Miracle-dz/UniFAR-FTUs huggingface dataset:
New Approach to Center of Mass Estimation for Humanoid Robots Based on Sensor Measurements and General LIPM

We present a center of mass estimator based on 6-axis force torque sensors and encoders. Acceleration of Center of Mass (CoM) is calculated using the total external forces. It is integrated to predict the CoM position and velocity. The forward kinematic equation and general Inverted Pendulum Model is used without any constraints on CoM height to update the states. The general model and equations handle changes of the height of CoM. This estimator is implemented on a simplified model of a humanoid robot in simulation. It is assumed that CoM of each link has some unknown offset errors. The estimator successfully compensates the offset errors besides the white noise in encoders and force torque sensors data, and finally estimates the CoM position on the ground.
Energy-Efficient Indirectly Heated Phase Change RF Switch

Linear radio-frequency (RF) switches are highly desired in wireless system front ends. Here, we report electro-thermal measurements and modeling of an indirectly heated phase change RF switch (IPCS). We study the energy-efficiency of the IPCS device by electro-thermal modeling and show that its layer design is crucial to reduce its switching power. Thermally optimized SbTe-based IPCS devices switch at a record-low power of ~8 mW/<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}^{2}$ </tex-math></inline-formula>, approaching the efficiency limit of such indirectly heated devices.
A Convergence and Asymptotic Analysis of Nonlinear Separation Model

Nonlinear blind source separation is the process of estimating either the original signals or mixture functions from the degraded signals, without any prior information about original sources. The key idea is to recover the sources by estimating an approximation function so as to approximate the inverse of mixing function. However, in practice, the approximation function is derived from some estimation algorithm with finite sample size, which leads to the performance loss. In this paper, we work on the convergence and asymptotic analysis of the separation approach, which uses the flexible approximation to extract the nonlinearity of mixture function so that to make the problem linearly separable. The analysis stems from the performance of a mismatched estimator that accesses the finite sample size. By providing a closed-form expression of normalized mean squared error (NMSE), we can present a novel algebraic formalization that leads to the upper bound on the estimation error. The simulation results show that if the flexible approximation can extract the nonlinearity of mixing functions, the minimized NMSE can be achieved as the sample size tends to be infinity. This implies that the algorithm is feasible to separate the distortion of the nonlinear mixture.
16.9 4.48GHz 0.18μm SiGe BiCMOS Exact-Frequency Fractional-N Frequency Synthesizer with Spurious-Tone Suppression Yielding a -80dBc In-Band Fractional Spur

The instantaneous divide value of the multimodulus divider in the feedback path of a fractional-N PLL is determined by a divider controller, which is usually implemented as a digital delta-sigma modulator $(\mathrm (D)\Delta \Sigma \mathrm (M))$. A disadvantage of the fractional-N PLL is the presence of fractional spurs, which result from interaction between the signal introduced by the $(\mathrm (D)\Delta \Sigma \mathrm (M))$ and nonlinearities in the loop. When fractional spurs at frequencies close to integer boundaries lie inside the loop bandwidth, they cannot be attenuated by filtering. The Successive Requantizer (SR) is an alternative to the $(\mathrm (D)\Delta \Sigma \mathrm (M))$-based divider controller, which randomizes the quantization process more effectively than $(\mathrm (D)\Delta \Sigma \mathrm (M))$. Wang et al. reported a worst-case in-band fractional spur of -64dBc in a 2.4GHz charge-pump PLL [1]. Liang and Wang reported a -70dBc worst-case fractional spur in a 2GHz analog PLL with a hybrid VCO and $(\mathrm (D)\Delta \Sigma \mathrm (M))$-based divider controller [2]. Familier and Galton improved the performance of the SR by implementing higher-order noise shaping. They achieved a worst-case fractional spur of -72dBc in a 3.3GHz analog PLL with a third-order SR [3]. The SR quantizes the frequency-control word one bit at a time, and, therefore, requires n stages in the case of an n-bit modulus. Thirunarayanan et al. implemented a hybrid MASH-SR divider-controller structure using four SR quantization blocks [4]. The divider-controller architecture described in this paper enables a 4.48GHz analog PLL to exhibit an in-band fractional spur of -80dBc and a -145dBc reference spur. It comprises a conventional MASH $(\mathrm (D)\Delta \Sigma \mathrm (M))$ followed by a programmable Probability Mass Redistributor (PMR). The PMR requantizes the output of the $(\mathrm (D)\Delta \Sigma \mathrm (M))$ and redistributes its samples in such a way that the in-band spurs are reduced by 7dB compared to the $(\mathrm (D)\Delta \Sigma \mathrm (M))$ alone.
Analyzing Modern Camera Response Functions

Camera Response Functions (CRFs) map the irradiance incident at a sensor pixel to an intensity value in the corresponding image pixel. The nonlinearity of CRFs impact physics-based and low-level computer vision methods like de-blurring, photometric stereo, etc. In addition, CRFs have been used for forensics to identify regions of an image spliced in from a different camera. Despite its importance, the process of radiometrically calibrating a camera's CRF is significantly harder and less standardized than geometric calibration. Competing methods use different mathematical models of the CRF, some of which are derived from an outdated dataset. We present a new dataset of 178 CRFs from modern digital cameras, derived from 1565 camera review images available online, and use it to answer a series of questions about CRFs. Which mathematical models are best for CRF estimation? How have they changed over time? And how unique are CRFs from camera to camera?
Energy Efficient Mobile Edge Computing using Joint Benders Decomposition and Distributed Dinkelbach Algorithm

Currently, executing computation intensive and time sensitive tasks among the network becomes a significant challenge. Traditional cloud computing executes the task with high latency and energy cost. Mobile edge computing (MEC) is proposed as a supplement to cloud computing. In this paper, we formulate a problem to minimize the energy cost in MEC, considering transmit power and latency constraints. To solve the proposed mixed integer nonlinear programming problem, we propose a joint Benders decomposition and distributed Dinkel-bach algorithm. The Benders decomposition performs as an outer loop algorithm, which separates the original problem into the subproblem and master problem. The distributed Dinkelbach algorithm solves subproblem in the inner loop in a distributed manner. The simulation results show that our proposed algorithm is energy efficient with high reliability.
Design and Analysis of EMI and RFI Suppressor for Induction Heating Equipment Using Vienna Rectifier

The proposed paper deals with the design and analysis of EMI and RFI suppressor for high frequency Induction Heating equipment (IHE) using Vienna Rectifier (VR). The simulations have been performed in PSIM software. The induction heating technology uses high frequency switching devices that are responsible for the generation of high frequency harmonics. The latter has an innate tendency to flow back towards the supply side which leads to the deterioration of the power quality. In this present work, an Induction Heating Equipment comprising of Vienna Rectifier has been proposed that a has much better harmonic attenuation ability than the existing ones using active and passive filters. The THD of the input current of an IHE with and without the application of VR has been compared to show the necessity and importance of the latter in the former. Moreover, attention has been paid off to the design of a controller for VR based on hysteresis comparators for its application in IHE.
CCL11 elicits secretion of RNases from mouse eosinophils and their cell‐free granules

Rapid secretion of eosinophil‐associated RNases (EARs), such as the human eosinophilic cationic protein (ECP), from intracellular granules is central to the role of eosinophils in allergic diseases and host immunity. Our knowledge regarding allergic inflammation has advanced based on mouse experimental models. However, unlike human eosinophils, capacities of mouse eosinophils to secrete granule proteins have been controversial. To study mechanisms of mouse eosinophil secretion and EAR release, we combined an RNase assay of mouse EARs with ultrastructural studies. In vitro, mouse eosinophils stimulated with the chemokine eotaxin‐1 (CCL11) secreted enzymatically active EARs (EC50 5 nM) by piecemeal degranulation. In vivo, in a mouse model of allergic airway inflammation, increased airway eosinophil infiltration (24‐fold) correlated with secretion of active RNases (3‐fold). Moreover, we found that eosinophilic inflammation in mice can involve eosinophil cytolysis and release of cell‐free granules. Cell‐free mouse eosinophil granules expressed functional CCR3 receptors and secreted their granule proteins, including EAR and eosinophil peroxidase in response to CCL11. Collectively, these data demonstrate chemokine‐dependent secretion of EARs from both intact mouse eosinophils and their cell‐free granules, findings pertinent to understanding the pathogenesis of eosinophil‐associated diseases, in which EARs are key factors. —Shamri, R. , Melo, R. C. N. , Young, K. M. , B. ‐B, M. , Xenakis, J. J., Spencer, L. A. , Weller, P. F. CCL11 elicits secretion of RNases from mouse eosinophils and their cell‐free granules. FASEB J. 26, 2084‐2093 (2012). www.fasebj. org
28.3 A 606μW mm-Scale Bluetooth Low-Energy Transmitter Using Co-Designed 3.5×3.5mm2 Loop Antenna and Transformer-Boost Power Oscillator

Wireless communication has been a limiting factor for achieving millimeter-sized wireless sensor nodes because of the high power consumption, large antenna size and off-chip components typically required. Several mm-scale radios have been proposed [1-3]; however, all use proprietary communication protocols, which afford their designers more flexibility to address the above challenges. For interoperability and ubiquitous adoption, it is important that mm-scale radios use standard protocols, such as Bluetooth Low Energy (BLE). However, implementing a BLE-compliant radio in a mm-scale form factor poses significant additional challenges. These include the requirements for center frequency deviation $( < 150$kHz), FSK modulation accuracy and frequency drift during the packet $( < 50$kHz), which drive up the power consumption of typical PLL + VCO + PA BLE transmitters to $> 3$mW [4- 5]. A 0.5mW BLE transmitter was achieved by relaxing these requirements, but suffered from high phase noise due to its low-power ring oscillator [6].
Complex-Valued and Quaternion Neural Networks to Deal with Complex Amplitude and Polarization: Their Strength in Electronics

This paper discusses the advantages in complex-valued and quaternion neural networks (CVNNs and QNNs) by presenting important concepts as well as applications in electronic engineering. Essentially, CVNNs and QNNs have excellent generalization ability in the learning of two- and three-dimensional rotation and scaling, respectively. Its origin is the sparsity in themselves as complex and quaternion numbers. The ability is useful in particular in adaptive processing of waves consisting of complex amplitude (amplitude and phase) and/or polarization. We consider an example in communications where we deal with channel prediction to discuss the superiority in CVNNs and its basics.
Repository : naistar Title Impact of Coding Style Checker on Code Review-A Case Study on the OpenStack Projects

Code review is key to ensuring the absence of potential issues in source code. Code review is changing from a costly manual check by reviewer to a cost-efficient automatic check by coding style checkers. So that patch authors can verify the changed code before submitting their patches. Although cost-efficiency, the checkers do not detect all potential issues, requiring reviewers to verify the submitted patches based on their knowledge. It would be most efficient if patch authors will learn potential issues and remove the same type of issues from patches prior to code review. This study investigates potential issues that patch authors have repeatedly introduced in their patch submissions despite receiving feedback. To understand the impact of adopting checkers to patch authors’ coding style improvement, this study compares two types of potential issues: Automatically Detected Issues by checkers (ADIs) and Manually Detected Issues by reviewers (MDIs). In a case study using an OpenStack code review dataset, we found that the patch authors have repeatedly introduced the same type of MDIs, while they do not repeat ADIs. This result suggests that the introduction of code style checkers might promote the patch authors’ effective potential issues learning.
Detecting Technology of Network Storage Covert Channel Based on OPTICS Algorithm

Nowadays, with our enhanced technology, network security has gradually been valued by more and more people. Network covert channel, as an important area of network security, was put forward these years. On the one hand, covert channels provide new and safe communication environment for network communication. However, on the other hand, some illegal persons are exploited to spread viruses, trojans, and so on. Therefore, the research on covert channels is particularly important. According to the resource attributes, network covert channels can be divided into two parts, storage-based channels and timestamps-based channels. The paper will base on the storage-based covert channels, and a new detection method based on clustering algorithm will be proposed. According to the clustering analysis of the values of various parts of the data flow packet, the clustering results are graphically displayed. Determine whether there is a covert channel in the packet. The experimental results show that the detection technology has the advantages of high accuracy, simple algorithm, and intuitive result images, and achieves the desired ideal results.
Automatic Generation of Warp-Level Primitives and Atomic Instructions for Fast and Portable Parallel Reduction on GPUs

Since the advent of GPU computing, GPU hardware has evolved at a fast pace. Since application performance heavily depends on the latest hardware improvements, performance portability is extremely challenging for GPU application library developers. Portability becomes even more difficult when new low-level instructions are added to the ISA (e.g., warp shuffle instructions) or the microarchitectural support for existing instructions is improved (e.g., atomic instructions). Library developers, besides re-tuning the code for new hardware features, deal with the performance portability issue by hand-writing multiple algorithm versions that leverage different instruction sets and microarchitectures. High-level programming frameworks and Domain Specific Languages (DSLs) do not typically support low-level instructions (e.g., warp shuffle and atomic instructions), so it is painful or even impossible for these programming systems to take advantage of the latest architectural improvements. In this work, we design a new set of high-level APIs and qualifiers, as well as specialized Abstract Syntax Tree (AST) transformations for high-level programming languages and DSLs. Our transformations enable warp shuffle instructions and atomic instructions (on global and shared memories) to be easily generated. We show a practical implementation of these transformations by building on Tangram, a high-level kernel synthesis framework. Using our new language and compiler extensions, we implement parallel reduction, a fundamental building block used in a wide range of algorithms. Parallel reduction is representative of the performance portability challenge, as its performance heavily depends on the latest hardware improvements. We compare our synthesized parallel reduction to another high-level programming framework and a hand-written high-performance library across three generations of GPU architectures, and show up to $7. 8 \times$ speedup $(2 \times$ on average) over hand-written code.
Current Ripples in Classical Predictive and Modified Dead-Beat Controller for PM Synchronous Motors-Analysis and Experimetal Results

A rapid change of applied voltage caused by high-nonlinear behavior of a voltage inverter results in motor phase current ripples. Classical Dead-Beat current controller for Permanent Magnet Synchronous Motor performs excellent for a wide range of speeds and torques but for some applications, if the current loading is extremely high, there is a need to modify main motor parameters used in Dead-Beat current controller model to avoid extreme current ripples. Paper tries to describe the phenomena in a more quantitative way. Levels of current ripples were systematically simulated for nominal motor parameters and set of distorted parameters. Experimental results verified obtained results and proved high performance of the proposed modified control algorithm.
Deriving Synthetic Filter Bank for Perfect Reconstruction of Light Field from Its Focal Stack

For 3D Lambertian scenes with no occlusion, we show that there exist a filter bank such that it can perfectly reconstruct the light field from the focal stack, if the focal stack is captured through “Cauchy-type” aperture mask. All the derived filters are spatially invariant; therefore the presented filter bank method requires no depth estimation. Simulation results using a synthetic scene show that the filter bank reconstructs the light field with significant high quality.
Motivation of Engineering Students with a Mixed-Contexts Approach to Introductory Programming

This research to practice full paper investigates motivation of engineering students with a mixed-contexts approach to introductory programming. Non-major CS1 students usually have more difficulties learning computer programming than CS majors, for reasons such as lack of interest in computing or courses formatted for CS majors. Student motivation is vital in the learning process, and fostering it is important to promote more effective learning. Various initiatives have been proposed to increase engagement and reduce the difficulties faced by non-majors in CS1 courses. We believe that motivation can be improved by using a mix of languages and tools already tested in CS1 teaching. In this paper, we evaluate a teaching approach for non-majors, which combines the use of Scratch in a context of game creation, and Python with both turtle graphics and image manipulation. We performed an exploratory case study with CS1 civil engineering students from our institution to analyze the impact of this approach on student motivation. Our results describe motivation arisen during the course in terms of attention, relevance, confidence and satisfaction (ARCS), and as practical factors that contribute to either increase or decrease motivation.
Investigation into the Use of Learning Agreements to Enhance Stakeholder Engagement and Promote Self-Efficacy in Computing Education

We examine controversial issues surrounding the locus of control in the implementation of learning agreements, plans or contracts, in the context of the U.K. university-level Graduate Apprenticeship scheme. We begin by giving an account of the stakeholders and their positions as well as their motivating principles as they strive to maintain their respective loci of control with regard to the negotiation of the learning agreement. We then describe the idiomatic challenges to implementation of a learning agreement and subsequent plan in work-based learning environments with a range of employers from different sectors. An investigation into the manner in which learning agreement tenets are changed due to competing pressures on the various stakeholders leads to a discussion of challenges to successful prioritisation of the learning plan that occur as a result of mutually exclusive requirement sets. We discuss the challenges that may present themselves in which the requirements of one set of stakeholders appear to conflict with others and the questions that are raised as those involved seek to ensure suitable standards of academic quality in difficult cases. Finally, we discuss whether learning agreements are the most appropriate operational instruments for maintaining standards in these circumstances.
8.6 A Fully Integrated 85%-Peak-Efficiency Hybrid Multi Ratio Resonant DC-DC Converter with 3.0-to-4.5V Input and 500μA -to-120mA Load Range

DC-DC converters for applications like wearables require an ultra-compact and flat module size. Hybrid converters are a promising converter class that supports integration of inductive and capacitive components, while minimizing losses and improving power density. Since many of these applications are often in sleep mode, high efficiency has to be achieved from high to low output power. Fully integrated 3-level buck converters [1, 2] do not maintain good efficiency over the full load range, since they operate at high switching frequencies, required for inductive PWM operation with small inductors. The converter in [3] achieves better efficiencies, but has a small conversion ratio. Resonant SC converters [4, 5] reach high efficiencies due to lower switching frequencies and better passive component utilization. However, low-power operation is not supported [1, 3–5] or it suffers from low efficiencies [2]. Moreover, only [4] supports a wide input voltage range based on mixed inductive and resonant operation, but still has an efficiency drop over varying input voltages. Hybrid converters, combining an SC cell with an external LC output filter, operated with inductive PWM control [6], achieve high efficiencies over wide input voltage, but they do not support low power operation.
22.5 A Bio-Impedance Readout IC With Digital-Assisted Baseline Cancellation for 2-Electrode Measurement

Recent advances in wearables allow for monitoring the health status of users without disturbing their daily lives (Fig. 22.5.1). Bio-Impedance (BIOZ) is an interesting sensing modality for impedance cardiography, respiration measurement, and body composition analysis [1–4]. However, existing solutions rely on a 4-electrode measurement, where two leads are used for the current generator (CG), and the others for the readout front-end (RFE). This eliminates the effect of the electrode-tissue impedance (ETI) and measures the actual BIOZ, which is required in body composition analysis where the absolute value is important. However, this degrades user comfort and adds to system complexity and cost. This work proposes a BIOZ readout IC supporting 2-electrode BIOZ measurement of body signals, where relative changes over time yields the desired information (heartrate, respiration, etc.), with a good accuracy as a 4-electrode setup (Fig. 22.5.1). The ASIC can even measure the heartrate at the wrist via 2 electrodes, which consumes significant less power than the Photoplethysmography.
Slam-Based 3D Outdoor Reconstructions From Lidar Data

The use of depth (RGBD) cameras to reconstruct large outdoor environments is not feasible due to lighting conditions and low depth range. LIDAR sensors can be used instead. Most state of the art SLAM methods are devoted to indoor environments and depth (RGBD) cameras. We have adapted two SLAM systems to work with LIDAR data. We have compared the systems for LIDAR and RGBD data by performing quantitative evaluations. Results show that the best method for LIDAR data is RTAB-Map with a clear difference. Additionally, RTAB-Map has been used to create 3D reconstructions with and without photometry from a visible color camera. This proves the potential of LIDAR sensors for the reconstruction of outdoor environments for immersion or audiovisual production applications.