Counting Scheme Research Articles

Wide Range SQUID Amplifier With Proportional Feedback for Flux Quanta Counting Scheme

To implement a flux quanta counting (FQC) scheme in the wide range magnetic field measurement using a superconducting quantum interference device (SQUID), we present a SQUID proportional feedback amplifier (PFA) circuit. It is a simplified version of the direct readout flux-locked loop (FLL) electronics without an integrator. It achieved a periodically repeated (with a period of 1Φ0), quasi-linear flux-to-voltage characteristics with an input range extended to 2Φ0. Its working point is reset spontaneously with 1Φ0 of flux jump caused by the over range flux input. The resultant wide range measurement is achieved by the synthesis of the PFA voltage output and the flux jumps recorded using the FQC scheme. We simulated and experimentally verified the working principles of SQUID PFA. The FQC scheme using SQUID PFA was demonstrated with measurements in both shielded and unshielded environment. SQUID PFA is simple and easy-to-operate suited for applications in the Earth's magnetic field.

Deterministic counting of graph colourings using sequences of subgraphs

AbstractIn this paper we propose a polynomial-time deterministic algorithm for approximately counting the k-colourings of the random graph G(n, d/n), for constant d>0. In particular, our algorithm computes in polynomial time a $(1\pm n^{-\Omega(1)})$ -approximation of the so-called ‘free energy’ of the k-colourings of G(n, d/n), for $k\geq (1+\varepsilon) d$ with probability $1-o(1)$ over the graph instances.Our algorithm uses spatial correlation decay to compute numerically estimates of marginals of the Gibbs distribution. Spatial correlation decay has been used in different counting schemes for deterministic counting. So far algorithms have exploited a certain kind of set-to-point correlation decay, e.g. the so-called Gibbs uniqueness. Here we deviate from this setting and exploit a point-to-point correlation decay. The spatial mixing requirement is that for a pair of vertices the correlation between their corresponding configurations becomes weaker with their distance.Furthermore, our approach generalizes in that it allows us to compute the Gibbs marginals for small sets of nearby vertices. Also, we establish a connection between the fluctuations of the number of colourings of G(n, d/n) and the fluctuations of the number of short cycles and edges in the graph.

Que-Fi: A Wi-Fi Deep-Learning-Based Queuing People Counting

The ubiquitous commercial Wi-Fi has brought unlimited possibilities to the smart city and the Internet of Things. Wi-Fi device-free sensing technology has received more and more attention in recent years. Counting the people in queuing is an uneasy task due to labile information. Most current counting schemes have existed in an ideal environment with idealistic people's behavior. In this article, we propose a more realistic counting scheme called Que-Fi, a queue number identification system based on Wi-Fi channel state information and a deep learning network. In the proposed Que-Fi scheme, the nonnegligible interference of human motion and the surrounding environment is first analyzed based on the Fresnel zone. Then, we proposed a static model based on the convolutional long short-term memory fully connected deep neural network in order to overcome the interference. A dynamic Que-Fi model is proposed to identify the entering/leaving people's behavior and update the counting number. In this article, different preprocessing methods are analyzed and compared to test and evaluate the proposed Que-Fi. Experiments have shown that the proposed Que-Fi outperforms the traditional support vector machine and provide accuracy up to 95% and 96.67% for static and dynamic models, respectively.

Probing the network topology in network-forming materials: The case of water

Rings statistic has been widely used to investigate the network topology in numerically simulated network-forming materials in order to rationalize their physical and mechanical properties. However, different topologies arise depending on how rings are counted, leading to incomplete or even contrasting physical interpretations. Solving this critical ambiguity is of primary importance for the correct assessment of material properties. Here, we show how such differences emerge in water, a complex network-forming material endowed with polyamorphism and a directional network of hydrogen bonds whose topology is correlated with the anomalous behavior of water. We probe the network in the liquid state at several thermodynamic points under equilibrium conditions, as well as during the out-of-equilibrium first-order-like low density to high density amorphous transformation. We study three schemes for counting rings and show that each of them provides complementary insightful information about the network, suggesting that a single counting scheme may not be sufficient to properly describe network topologies and to assess material properties. Our results provide a molecular description of the rings in supercooled water and of the amorphous-to-amorphous transformation kinetics, hence shedding light on the complex nature of water. Nonetheless, our results expose how delicate the proper choice of method for counting rings is, an issue with important consequences for rationalizing the properties of network-forming materials at large.

Mark Mansel Rehfisch (11 October 1960 – 8 October 2019)

Mark Mansel Rehfisch (11 October 1960 – 8 October 2019)

A 0.025-mm2 0.8-V 78.5-dB SNDR VCO-Based Sensor Readout Circuit in a Hybrid PLL-$\Delta\Sigma$ M Structure

This article presents a capacitively coupled voltage-controlled oscillator (VCO)-based sensor readout featuring a hybrid phase-locked loop (PLL)-ΔΣ modulator structure. It leverages phase-locking and phase-frequency detector (PFD) array to concurrently perform quantization and dynamic element matching (DEM), much-reducing hardware/power compared with the existing VCO-based readouts' counting scheme. A low-cost in-cell data-weighted averaging (DWA) scheme is presented to enable a highly linear tri-level digital-to-analog converter (DAC). Fabricated in 40-nm CMOS, the prototype readout achieves 78-dB SNDR in 10-kHz bandwidth, consuming 4.68 μW and 0.025-mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> active area. With 172-dB Schreier figure of merit, its efficiency advances the state-of-the-art VCO-based readouts by 50×.

Learning of Counting Crowded Birds of Various Scales via Novel Density Activation Maps

The previous counting methods trained by the density map regression scheme fail to precisely count the number of birds in crowded bird images of various scales. This is due to the coarseness of the manually created target density maps. In this paper, we propose a new counting scheme, called DAM counting, which generates our-first-proposed density activation map (DAM). DAM is a CNN perspective density map that has high activation values where the network focuses on for precise counting of birds. The network is trained to autonomously learn where and how much the DAM should be activated so that the sum of all values in the DAM estimates the number of birds. Moreover, our DAM counting scheme incorporates two segmentation regularizers that enable precise counting of birds with various scales and appearance. Our DAM counting scheme can effectively substitute the existing density map regression scheme, bringing in a remarkable increase of 45% in the counting accuracy. We also propose the first crowded bird dataset, called CBD-6000, which is very valuable for crowded bird counting research.

Digital counting of nucleic acid targets using solid-state nanopores.

Assays targeting biomarkers for the early diagnosis of disease demand a sensing platform with a high degree of specificity and sensitivity. In this work, we developed and characterized a solid-state nanopore-based sensing assay for the detection of short nucleic acid targets with readily customizable nanostructured DNA probe sets. We explored the electrical signatures of three DNA nanostructures to determine their performance as probe sets in a digital counting scheme to quantify the concentration of targets. With these probes, we demonstrate the specific, simultaneous detection of two different DNA targets in a 2-plex assay, and separately that of microRNA-155, a biomarker linked to various human cancers. In addition to specific target detection, our scheme demonstrated the ability to quantify at least six different microRNA concentrations. These results highlight the potential for solid-state nanopores as single-molecule counters for future digital diagnostic technologies.

On the Distribution of the Number of Success Runs in a Continuous Time Markov Chain

We propose a continuous-time adaptation of the well-known concept of success runs by considering a marked point process with two types of marks (success-failure) that appear according to an appropriate continuous-time Markov chain. By constructing a bivariate imbedded process (consisting of a run-counting and a phase process), we offer recursive formulas and generating functions for the distribution of the number of runs and the waiting time until the appearance of the n-th success run. We investigate the three most popular counting schemes: (i) overlapping runs of length k, (ii) non-overlapping runs of length k and (iii) runs of length at least k. We also present examples of applications regarding: the total penalty cost in a maintenance reliability system, the number of risky situations in a non-life insurance portfolio and the number of runs of increasing (or decreasing) asset price movements in high-frequency financial data.

A 102.2-dB, 181.1-dB FoM Extended Counting Analog-to-Digital Converter With Capacitor Scaling

Sensor interfaces demand ever-increasing energy efficiency from analog-to-digital converters (ADCs). For sensors requiring a wide dynamic range (DR) (>12 bit), the incremental ADC (IADC) is becoming a popular choice. In this article, the design of an energy-efficient IADC with a 16-bit signal-to-noise and distortion ratio (SNDR) and 17-bit DR is described. The IADC implements a novel capacitor scaling technique, which reduces power consumption in the critical first operational transconductance amplifier (OTA) by up to 37%. The new technique can be combined with the extended counting (EC) scheme utilizing an in-loop 4-bit asynchronous successive approximation register (SAR) (ASAR) ADC. Using a three-phase operation, this IADC architecture further reduces the power while enabling wider signal bandwidth with a much lower oversampling ratio (OSR). Silicon measurements in a 0.18- $\mu $ m CMOS process show the IADC achieved a DR of 102.2 dB, within a bandwidth of 2.04 kHz, with power consumption of about $25~\mu $ W, leading to a state-of-the-art Schreier figure-of-merit (FoM) of 181.1 dB.

IDENTIFIKASI KEMAMPUAN BERHITUNG PADA MATERI PENJUMLAHAN BERDASARKAN COUNTING ON DI SD MUHAMMADIYAH 2 TARAKAN

This study aims to identify the level of students' mathematical arithmetic skills in solving problems in the summing material based on counting on in class II of SD Negeri 018 Tarakan. The method used is a quantitative approach to the type of descriptive explanation. The results of the study were obtained from the students' numeracy ability test results based on the mathematics numeracy ability category of students in the high and medium categories. The problems used to identify the ability to count scheme are three problems, namely problems related to counting on, counting all, then counting on and counting all. The results of students' math skills based on the counting on scheme were obtained through interviews with 25 research subjects. Problem 1 was solved by students with a counting scheme of 10 students (40%), Problem 2 was solved by students with a counting scheme of 1 student (4%). Problem 3 is solved by students with a counting on scheme of 2 students (8%).

A 25-MHz Four-Phase SAW Hysteretic Control DC–DC Converter With 1-Cycle Active Phase Count

In order to meet stringent power requirements in modern application processors, a 25-MHz four-phase dc–dc power converter is presented. It employs an adaptive window hysteretic control to facilitate ultra-fast transient response and minimize output voltage ( $V_{O}$ ) undershoot and overshoot during load transient periods. Inherent clock synchronization ability ensures current balancing between phase sub-converters. The control also enables a wide range of programmable $V_{O}$ for dynamic voltage/frequency scaling. To maintain high efficiency over a wide power range without degrading transient speed, a 1-cycle active phase count scheme is introduced. A design prototype was fabricated in a 0.35- $\mu \text{m}$ CMOS process with an active die of 1.88 mm2. Simple circuit structure benefits a power density of 3.98 W/mm2. At a switching frequency of 25 MHz and a nominal input of 3.3 V, it regulates a programmable $V_{O}$ ranging from 0.3 to 2.5 V. It achieves more than 80% efficiency over 96.7% of power range with a peak value of 88.1%. In response to 4-A load step-up/down, it achieves 103 mV/123 mV $V_{O}$ undershoot/overshoot with 1% settling time of 190 ns/237 ns, respectively.

Revisiting Bond Breaking and Making in EuCo2 P2 : Where are the Electrons?

X-ray absorption spectroscopy (XAS) was used to elucidate changes in the electronic structure caused by the pressure-induced structural collapse in EuCo2 P2 . The spectral changes observed at the L3 -edge of Eu and K-edges of Co and P suggest electron density redistribution, which contradicts the formal charges calculated from the commonly used Zintl-Klemm concept. Quantum-chemical calculations show that, despite the increase in the oxidation state of Eu and the formation of a weak P-P bond in the high-pressure phase, the electron transfer from the Eu 4f orbitals to the hybridized 5d and 6s states causes strengthening of the Eu-P and P-P bonds. These changes explain the increased electron density on P atoms, deduced from the P K-edge XAS spectra. This work shows that the formal electron counting schemes do not provide an adequate description of changes associated with phase transitions in metallic systems with substantial mixing of the electronic states.

A Multiquark Approach to Excited Hadrons and Regge Trajectories

We propose a novel approach to construction of hadron spectroscopy. The case of light nonstrange mesons is considered. By assumption, all such mesons above 1 GeV appear due to creation of constituent quark-antiquark pairs inside π or ρ(ω) mesons. These spin-singlet or triplet pairs dictate the quantum numbers of formed resonance. The resulting classification of light mesons turns out to be in a better agreement with the experimental observations than the standard quark model classification. It is argued that the total energy of quark components should be proportional to the hadron mass squared rather than the linear mass. As a byproduct a certain relation expressing the constituent quark mass via the gluon and quark condensate is put forward. We show that our approach leads to an effective mass counting scheme for meson spectrum and results in the linear Regge and radial Regge trajectories by construction. An experimental observation of these trajectories might thus serve as evidence not for string but for multiquark structure of highly excited hadrons.

Fragility and aging behavior of SixSe1-x glasses and liquids.

The composition dependence of the fragility of SixSe1-x liquids with 0.05 ≤ x ≤ 0.33 is determined using the calorimetric method and is found to be rather similar to that characteristic of their Ge analogues. In addition, the nature and the time scale of the structural relaxation of the Si25Se75 glass during aging at 40 K below Tg are measured using Raman spectroscopy. The structural relaxation in this glass, which belongs to the so-called intermediate phase, involves progressive conversion of the doubly edge-shared SiSe4/2 tetrahedra E2 into singly edge-shared E1 and corner-shared E0 tetrahedra upon lowering of temperature. This tetrahedral speciation can be expressed in the form of the reaction 2 E2 → E0 + E1. The time scale of this tetrahedral conversion reaction corresponds well with that of shear relaxation. This result is inconsistent with the claim made previously in the literature that intermediate phase compositions do not undergo aging. Moreover, when taken together, the fragility and the structural relaxation results suggest that the constraint counting scheme typically adopted in the literature for edge- vs. corner-shared tetrahedra in chalcogenide networks may need to be revised. A rigid-polytope based constraint counting approach is shown to be more consistent with the experimental results.

A Triple-Mode Performance-Optimized Reconfigurable Incremental ADC for Smart Sensor Applications

This paper proposes a triple-mode discrete-time incremental analog-to-digital converter (IADC) employing successive approximation register (SAR)-based zooming and extended counting (EC) schemes to achieve programmable trade-off capability of resolution and power consumption in various smart sensor applications. It mainly consists of an incremental delta–sigma modulator and the proposed SAR-EC sub-ADC for alternate operation of the coarse SAR conversion and EC. They can be reconfigured to operate separately depending on the application requirements. The SAR-based zooming structure allows the IADC to have better linearity and resolution, and additional activation of the EC function gives the further resolution. During this reconfigurable conversion process, pipelined reusing operation of sub-blocks reduces the silicon area and the number of cycles for target resolutions. A prototype ADC is fabricated in a 180-nm CMOS process, and its triple-mode operation of high-resolution, medium-resolution, and low-power is experimentally verified to achieve 116.1-, 109.4-, and 73.3-dB dynamic ranges, consuming 1.60, 1.26, and 0.39 mW, respectively.

A Recent Trend in Individual Counting Approach Using Deep Network

In video surveillance scheme, counting individuals is regarded as a crucial task. Of all the individual counting techniques in existence, the regression technique can offer enhanced performance under overcrowded area. However, this technique is unable to specify the details of counting individual such that it fails in locating the individual. On contrary, the density map approach is very effective to overcome the counting problems in various situations such as heavy overlapping and low resolution. Nevertheless, this approach may break down in cases when only the heads of individuals appear in video scenes, and it is also restricted to the feature’s types. The popular technique to obtain the pertinent information automatically is Convolutional Neural Network (CNN). However, the CNN based counting scheme is unable to sufficiently tackle three difficulties, namely, distributions of non-uniform density, changes of scale and variation of drastic scale. In this study, we cater a review on current counting techniques which are in correlation with deep net in different applications of crowded scene. The goal of this work is to specify the effectiveness of CNN applied on popular individuals counting approaches for attaining higher precision results.

Low-energy lepton-proton bremsstrahlung via effective field theory

We present a systematic calculation of the cross section for the lepton-proton bremsstrahlung process l + p --> l' + p + gamma in chiral perturbation theory at next-to-leading order. This process corresponds to an undetected background signal for the proposed MUSE experiment at PSI. MUSE is designed to measure elastic scattering of low-energy electrons and muons off a proton target in order to extract a precise value of the proton's r.m.s. radius. We show that the commonly used peaking approximation, which is used to evaluate the radiative tail for the elastic cross section, is not applicable for muon-proton scattering at the low-energy MUSE kinematics. Furthermore, we point out a certain pathology with the standard chiral power counting scheme associated with electron scattering, whereby the next-to-next-to-leading order contribution from the pion loop diagrams is kinematically enhanced and numerically of the same magnitude as the next-to-leading order corrections. We correct a misprint in a commonly cited review article.

Device-free occupancy detection and crowd counting in smart buildings with WiFi-enabled IoT

Precise occupancy information is extremely valuable for energy savings and optimization in the built environment. Building management systems (BMSs) can automatically turn off the HVAC systems in unoccupied spaces and adjust the ventilation rate based on the number of occupants in each zone for energy saving. Popular commercial occupancy detection and crowd counting approaches, such as the infrared sensor, camera, and mobile devices, either require the deployment of extra infrastructure or the cooperation of occupants to carry dedicated devices, which are intrusive and inconvenient for pervasive implementation. In this paper, we propose WiFree, a novel device-free occupancy detection and crowd counting scheme using only commercial WiFi enabled the Internet of Things (IoT) devices. Firstly, we design a novel IoT platform with which the fine-grand channel state information (CSI) measurements can be obtained directly from pervasive IoT devices. Given the CSI data, we propose an effective occupancy detection scheme by measuring the shape similarity between adjacent time series CSI curves. For crowd counting, we first design an information theory based feature selection scheme to select the most representative features that are sensitive to human motion. After that, we propose a crowd counting classifier based on transfer kernel learning and information fusion, which is robust to temporal and environmental disparities. We implemented WiFree with commodity WiFi routers and conducted extensive experiments in three indoor environments of disparate sizes. Experimental results have validated that WiFree is able to achieve 99.1% occupancy detection accuracy and 92.8% crowd counting accuracy over temporal variation in a device-free and privacy-preserving manner.

The Crystal Orbital Hamilton Population (COHP) Method as a Tool to Visualize and Analyze Chemical Bonding in Intermetallic Compounds

Recognizing the bonding situations in chemical compounds is of fundamental interest for materials design because this very knowledge allows us to understand the sheer existence of a material and the structural arrangement of its constituting atoms. Since its definition 25 years ago, the Crystal Orbital Hamilton Population (COHP) method has been established as an efficient and reliable tool to extract the chemical-bonding information based on electronic-structure calculations of various quantum-chemical types. In this review, we present a brief introduction into the theoretical background of the COHP method and illustrate the latter by diverse applications, in particular by looking at representatives of the class of (polar) intermetallic compounds, usually considered as “black sheep” in the light of valence-electron counting schemes.