Analog Processing Research Articles

Digitalization of fitness and sports

Digitalization is the process of transforming analogue technologies and processes into digital ones. These transformations are expressed in the deep penetration of digital technologies into all processes of the sports industry, their optimisation, increased productivity, and improved communication with consumers. The digitalization process is driving changes in society that have both technological, economic, and social aspects. The purpose of the article is to explore the aspects and impact of digitalization on the fitness and sports sectors and to identify opportunities, challenges, and directions for the development of the sports industry created by digitalization. Research methods: theoretical analysis, systematisation, and generalisation of scientific and methodological literature in the field of fitness and sports. Results of the study. The digitalization of fitness and sports is a trend that is gaining popularity both in Ukraine and around the world. The market for digital products and services in the sports industry will continue to grow. And understanding the latest trends and using digital tools will become key competencies for professionals in this industry in the future. Conclusions. Digitalization has made sports more accessible; it has allowed coaches, athletes, and fitness enthusiasts to obtain more accurate and individualised data about their training and increase its effectiveness. For fitness facilities and sports organisations, the use of digital tools creates opportunities to expand their audience, improve customer performance, enhance the quality of their services, and, as a result, increase revenue. For national sports federations, the digitalization process will help them regain institutional capacity, simplify reporting, make their activities more transparent and public, which will reduce corruption risks, and accelerate the development of domestic IT technologies in the field of physical culture and sports.

Developing an instrument to examine students' analogical modeling competence: An example of electricity

AbstractScience education reforms advocate modeling as a core practice in which analogy is a significant form and analogical modeling is a creative process for scientific explanation and discovery. This study adopts the self‐generated analogical modeling approach involving electricity, which considers all the modeling subprocesses and includes two subtopics (circuits and energy) with incompatible ontological presuppositions as a conceptual space to develop an analogical modeling competence (AMC) instrument. Two constructs, phenomenon‐related abductive premises (Phenomenon‐AbPr) and analogical modeling processes (AMP), that describe the increasing sophistication of students' AMC (i.e., Level 0 experience to Level 4 high‐order relation) are considered. The procedures utilize a construct‐based approach of developing an assessment to validate the underlying constructs and subtopics to develop the mapping between the target and the analogical models, design items, and determine outcome spaces. Data were collected from 294 Grade 6 students to examine their AMC. The item response theory technique based on the Rasch partial credit model was used to validate the two‐phase model. Student results revealed that the infit and outfit mean square values were between 0.75 and 1.33, indicating acceptable item fit. Results revealed that students scored highest on the open series circuit and lowest on electric energy in the Phenomenon‐AbPr phase. Most students demonstrated relational mapping in the analogical model validation (Level 3) stage, which performed best in the AMP phase. However, they struggled to transfer factors during the analogical model application and deployment (Level 0). Implications for science assessment and teaching are discussed.

Review and Analysis of Beamforming's Power Allocation Studies for (5G) Networks

The necessity to investigate viable spectrum areas for satisfying the anticipated needs has been prompted by the rising cellular data traffic demands. As a result, the scientific community has given (mmWave) communication a lot of attention. In (5G) wireless networks, massive (mmWave MIMO) communications are often accomplished using hybrid transceivers that combine lower and higher as a digital and analog processing units phase shifters and power amplifiers respectfully. This hybrid beamforming (HB) architecture lowers costs and power use, which is consistent with the (5G) network's objective for (EE) of design. In this work, using system models of hybrid transceiver architectures, both digital (DB) and analog (AB) beamforming arrays with possibilities for antenna design, and hybrid beamforming (HB) in heterogeneous wireless networks, they trace the development of (HB) for massive MIMO connections. Authors widen in discussion by focusing on hybrid beamforming to solve resource management issue and examine the applicability of hybrid beamforming (HB) techniques while also highlighting the fascinating difficulties that lie ahead for this field. The main aim of this work is to analyse the many studies and show the advantages and weak points of each single study based on the general and famous parameters as well as explaining the efficiency of all studies. We got an overview of the hybrid beamforming, which covers topics such as application areas; In order to reduce upfront costs and continuing operating costs, the fully-connected architecture can achieve full beamforming gain per RF chain, but at the expense of increased hardware complexity. On the other hand, the low-complexity sub-connected architecture offers reduced beamforming gain.

Time derivatives via interconnected waveguides

Electromagnetic wave-based analogue computing has become an interesting computing paradigm demonstrating the potential for high-throughput, low power, and parallel operations. In this work, we propose a technique for the calculation of derivatives of temporal signals by exploiting transmission line techniques. We consider multiple interconnected waveguides (with some of them being closed-ended stubs) forming junctions. The transmission coefficient of the proposed structure is then tailored by controlling the length and number of stubs at the junction, such that the differentiation operation is applied directly onto the envelope of an incident signal sinusoidally modulated in the time domain. The physics behind the proposed structure is explained in detail and a full theoretical description of this operation is presented, demonstrating how this technique can be used to calculate higher order or even fractional temporal derivatives. We envision that these results may enable the development of further time domain wave-based analogue processors by exploiting waveguide junctions, opening new opportunities for wave-based single operators and systems.

Continuum Logic of Control Signals in Analog Cyber–Physical Nets

The use of embedded processors is the most promising direction in the development of automatic control systems. The article is devoted to analog models and technical solutions that allow continuous analysis of information in a technical system in order to synthesize control signals. Technical solutions are obtained on the basis of continuum logic methods, which aim to increase the speed of embedded computing networks, reduce power consumption, and unify the element base of analog processors. The effect of high speed is achieved due to the transition from sequential digital calculations to parallel synthesis of analog control signals. Examples of the implementation of schemes for the synthesis of control commands using the developed models of logical operations are given.

Hydrophobically driven hosting – What about the guest?

The hosting of cyclic and linear aliphatic moieties by cucurbit[7]uril and β-cyclodextrin was investigated by means of ITC, 2D ROESY NMR spectroscopy, and by classical MD simulations. The cyclodextrin complexation thermodynamics at 298 K revealed classical hydration of the investigated guests. The results of the comparative calorimetric study clearly pointed out that the dehydration of cucurbituril cavity is accompanied with lower entropy changes compared to the analogous process involving cyclodextrin. A pronounced temperature dependence of ΔrH° (hence ΔrS°) unaccompanied by changes in product structure was observed for all studied systems. The effect was primarily due to temperature-induced disordering of the guest-hydrating water, i.e. gradual change from classical- towards non-classical hydration of the aliphatic moieties. The study thus reveals the effect of the guest and the cavity dehydration on the complexation thermodynamics while simultaneously providing rationale bridging the classical and non-classical hydrophobic effect. The obtained results also indicate that closer examination of the temperature influence on the corresponding complexation equilibria could further enhance the utilisation of the thermodynamic potential of hydrophobically driven association and result in a better understanding of water solvation properties.

The computational power of the human brain.

At the end of the 20th century, analog systems in computer science have been widely replaced by digital systems due to their higher computing power. Nevertheless, the question keeps being intriguing until now: is the brain analog or digital? Initially, the latter has been favored, considering it as a Turing machine that works like a digital computer. However, more recently, digital and analog processes have been combined to implant human behavior in robots, endowing them with artificial intelligence (AI). Therefore, we think it is timely to compare mathematical models with the biology of computation in the brain. To this end, digital and analog processes clearly identified in cellular and molecular interactions in the Central Nervous System are highlighted. But above that, we try to pinpoint reasons distinguishing in silico computation from salient features of biological computation. First, genuinely analog information processing has been observed in electrical synapses and through gap junctions, the latter both in neurons and astrocytes. Apparently opposed to that, neuronal action potentials (APs) or spikes represent clearly digital events, like the yes/no or 1/0 of a Turing machine. However, spikes are rarely uniform, but can vary in amplitude and widths, which has significant, differential effects on transmitter release at the presynaptic terminal, where notwithstanding the quantal (vesicular) release itself is digital. Conversely, at the dendritic site of the postsynaptic neuron, there are numerous analog events of computation. Moreover, synaptic transmission of information is not only neuronal, but heavily influenced by astrocytes tightly ensheathing the majority of synapses in brain (tripartite synapse). At least at this point, LTP and LTD modifying synaptic plasticity and believed to induce short and long-term memory processes including consolidation (equivalent to RAM and ROM in electronic devices) have to be discussed. The present knowledge of how the brain stores and retrieves memories includes a variety of options (e.g., neuronal network oscillations, engram cells, astrocytic syncytium). Also epigenetic features play crucial roles in memory formation and its consolidation, which necessarily guides to molecular events like gene transcription and translation. In conclusion, brain computation is not only digital or analog, or a combination of both, but encompasses features in parallel, and of higher orders of complexity.

Vibration Measurements by Self-Mixing Interferometry: An Overview of Configurations and Benchmark Performances

Self-mixing interferometry (SMI) is suitable to sense and measure vibrations of amplitudes ranging from picometers to millimeters at frequencies from sub-Hz to MHz’s. As an optical probe, SMI has the advantage of being non-invasive with the ability to measure without any treatment of the target surface and operate from a substantial standoff distance from the target. As an additional advantage, the SMI configuration is much simpler than that of conventional interferometers as it does not require any optical part external to the laser source. After a short introduction to the basics of SMI, we review the development of configurations of SMI instruments for vibration measurements, based on both analog and digital processing, with record performance to cover the range of vibration amplitudes from 0.1 nm to 1 mm, frequencies up to MHz, and stand-off distances up to 100 m. These performances set a benchmark that is unequaled by other approaches reported so far in the literature. The configurations we describe are (i) a simple MEMS-response testing instrument based on fringe counting, (ii) a half-fringe locking vibrometer for mechanical mode analysis and transfer function measurements, with a wide linear response on six decades of amplitude, (iii) a vibrometer with analog switching cancellation for μm-to-mm amplitude of vibrations, and (iv) a long standoff distance vibrometer for testing large structures at distances up to 100 m and with nm sensitivity. Lastly, as the vibrometer will almost invariably operate on untreated, diffusing surfaces, we provide an evaluation of phase-induced speckle pattern errors affecting the SMI measurement.

Toward Terabit Receivers for Optical and Wireless Communications

Data rates and bandwidths in global optical communication networks and their wireless access are continuously rising as a result of new applications. Besides communication, high bandwidth devices are also needed for radar, sensors and measurement systems. These increasing bandwidths might lead to problems for the electronic analog-to-digital converters (ADC) in the digital systems. A 1Tbit/s, 16-QAM modulated data signal, for instance, needs an analog processing bandwidth of 80 GHz, which is far beyond the possibilities of today's standard CMOS technology. Additionally, higher bandwidths are accompanied by a lower conversion resolution, which requires higher signal-to-noise ratios for the signals to be detectable. Here we discuss these connections and review possibilities for a solution by a photonics assisted parallelization of the incoming high bandwidth signal into several low bandwidth sub-signals in the time and frequency domain. These sub-signals can then be detected and processed with low bandwidth electronics, circumventing the CMOS bandwidth problem. This review primarily focuses on bandwidth reduction using time-frequency coherence. Since it only needs low bandwidth standard electronics and photonics, the seamless integration with the electronic ADCs into any electronic-photonic platform is straightforward. Therefore, it could become an important component of future terabit receivers in optical and wireless communication.

Simulation of machining behaviour of two-phase brittle materials during grinding by modelling single-grain scratching using a combination of FE and SPH methods

Two-phase, brittle-hard materials are widely used not only in the tool industry but also increasingly in the aerospace industry. Due to the two-phase nature, the materials have unique material properties adapted to the respective application. But the material properties also lead to challenging machinability. Therefore, two-phase, brittle-hard materials are mostly ground. The analogy process of single-grain scratching is used to analyse the material removal behaviour and design the grinding process. Since single-grain scratching is time-consuming and costly, it is desirable to substitute the analogy process with numerical simulation. This paper discusses the suitability of the Smooth Particle Hydrodynamic (SPH) simulation method in combination with the Finite Element Method (FEM) for single-grain scratching of two-phase, brittle-hard materials. The approach is validated using the examples of tungsten carbide-cobalt (WC-Co) cemented carbides and Silicon carbide fibre-reinforced silicon carbide (SiC/SiC) ceramics. For both applications, the material removal behaviour was optically analysed and in good agreement with the experimental results and theoretical assumptions. For SiC/SiC ceramics, several surface phenomena could be identified in the simulation as well as in the experimental results. The scratching forces were compared qualitatively and were in good agreement with the experimental results for both applications.

GENERATION OF MPSK SIGNAL USING LOGIC CIRCUITS

The traditional technique of generating MPSK signals is basically to use IQ modulator that involves analog processing like multiplication and addition where inaccuracies may exist and would lead to imbalance problems that affects the output modulated signal and hence the overall performance of the system. In this paper, a simple method is presented for generating the MPSK using logic circuits that basically generated M-carrier signals each carrier of different equally spaced phase shift. Then these carriers are time multiplexed, according to the data symbols, into the output modulated signal.

Imprinting: expanding the extra-pharmacological model of psychedelic drug action to incorporate delayed influences of sets and settings.

Psychedelic drug experiences are shaped by current-moment contextual factors, commonly categorized as internal (set) and external (setting). Potential influences of past environments, however, have received little attention. To investigate how previous environmental stimuli shaped the experiences of patients receiving ketamine for treatment-resistant depression (TRD), and develop the concept of "imprinting" to account for such time-lagged effects across diverse hallucinogenic drugs. Recordings of treatment sessions and phenomenological interviews from 26 participants of a clinical trial investigating serial intravenous ketamine infusions for TRD, conducted from January 2021 to August 2022, were retrospectively reviewed. A broad literature search was undertaken to identify potentially underrecognized examples of imprinting with both serotonergic and atypical psychedelics, as well as analogous cognitive processes and neural mechanisms. In naturalistic single-subject experiments of a 28-year-old female and a 34-year-old male, subjective ketamine experiences were significantly altered by varying exposures to particular forms of digital media in the days preceding treatments. Higher levels of media exposure reduced the mystical/emotional qualities of subsequent psychedelic ketamine experiences, overpowering standard intention-setting practices and altering therapeutic outcomes. Qualitative data from 24 additional patients yielded eight further spontaneous reports of past environmental exposures manifesting as visual hallucinations during ketamine experiences. We identified similar examples of imprinting with diverse psychoactive drugs in past publications, including in the first-ever report of ketamine in human subjects, as well as analogous processes known to underly dreaming. Past environmental exposures can significantly influence the phenomenology and therapeutic outcomes of psychedelic experiences, yet are underrecognized and understudied. To facilitate future research, we propose expanding the contextual model of psychedelic drug actions to incorporate imprinting, a novel concept that may aid clinicians, patients, and researchers to better understand psychedelic drug effects. ClinicalTrials.gov, identifier NCT04701866.

The Origin of Friulanisms of the Type medih ‘doctor’ and lampadarih ‘chandelier’ in Dialectal Slovenian in the Slavic-Romance Contact Area in Friuli

The article discusses the origin of the nominal forms ending in -ih [iχ] of the type medih ‘doctor’ and lampadarih ‘chandelier’ in dialectal Slovenian on the Slovenian-Friulian language boundary. Regarding their origin, these forms represent loanwords from Friulian, where they typically end in -i (cf. Friul. mièdi ‘doctor’, lampadàri ‘chandelier’), reflecting their original Romance pre-forms MEDICU(M) and LAMPADĀRIU(M). The contribution tries to account for the presence of the voiceless velar fricative h [χ] in both groups of borrowings, taking into consideration the linguistic history of both Friulian and Slovenian. While the voiceless velar fricative χ in the medih-type can most probably be explained by assuming a more archaic phonetic reflex of the original MEDICU(M) in Old Friulian, the origin of χ in the lampadarih-type seems to be the result of analogical processes in the linguistic history of Slovenian.

Sentiment Analysis of Digital Television Migration on Twitter Using Naïve Bayes Multinomial Comparison, Support Vector Machines, and Logistic Regression Algorithms

The Ministry of Communication and Information Technology (KEMENKOMINFO) has announced to the publics in Indonesia regarding the termination of analog television broadcasts or called analog switch-off, which requires the public to migrate from analog television to digital television. Regarding the process of stopping analog broadcasts this raises pros and cons by the people in Indonesia. Many people give their respective opinions through social media, especially on Twitter. A collection of pros and cons data from the public can be collected and used as research of sentiment analysis. This research will focus on comparing three classification algorithms, which is called Multinomial Naïve Bayes, Support Vector Machines, and Logistic Regression using the same dataset and the same method called Lexicon Based. The results showed that the highest accuracy is Support Vector Machines with the accuracy is 94.00%, Logistic Regression with the accuracy is 90.00%, and Multinomial Naïve Bayes with the accuracy is 88.00%.

Modified Smoluchowski Rate Equations for Aggregation and Fragmentation in Finite Systems.

Protein self-assembly into supramolecular structures is important for cell biology. Theoretical methods employed to investigate protein aggregation and analogous processes include molecular dynamics simulations, stochastic models, and deterministic rate equations based on the mass-action law. In molecular dynamics simulations, the computation cost limits the system size, simulation length, and number of simulation repeats. Therefore, it is of practical interest to develop new methods for the kinetic analysis of simulations. In this work we consider the Smoluchowski rate equations modified to account for reversible aggregation in finite systems. We present several examples and argue that the modified Smoluchowski equations combined with Monte Carlo simulations of the corresponding master equation provide an effective tool for developing kinetic models of peptide aggregation in molecular dynamics simulations.

Distinct microbial structure and metabolic potential shaped by significant environmental gradient impacted by ferrous slag weathering

Alkaline ferrous slags pose global environmental issues and long-term risks to ambient environments. To explore the under-investigated microbial structure and biogeochemistry in such unique ecosystems, combined geochemical, microbial, ecological and metagenomic analyses were performed in the areas adjacent to a ferrous slag disposal plant in Sichuan, China. Different levels of exposure to ultrabasic slag leachate had resulted in a significant geochemical gradient of pH (8.0–12.4), electric potential (−126.9 to 437.9 mV), total organic carbon (TOC, 1.5–17.3 mg/L), and total nitrogen (TN, 0.17–1.01 mg/L). Distinct microbial communities were observed depending on their exposure to the strongly alkaline leachate. High pH and Ca2+ concentrations were associated with low microbial diversity and enrichment of bacterial classes Gamma-proteobacteria and Deinococci in the microbial communities exposed to the leachate. Combined metagenomic analyses of 4 leachate-unimpacted and 2-impacted microbial communities led to the assembly of one Serpentinomonas pangenome and 81 phylogenetically diversified metagenome assembled genomes (MAGs). The prevailing taxa in the leachate-impacted habitats (e.g., Serpentinomonas and Meiothermus spp.) were phylogenetically related to those in active serpentinizing ecosystems, suggesting the analogous processes between the man-made and natural systems. More importantly, they accounted for significant abundance of most functional genes associated with environmental adaptation and major element cycling. Their metabolic potential (e.g., cation/H+ antiporters, carbon fixation on lithospheric carbon source, and respiration coupling sulfur oxidization and oxygen or nitrate reduction) may support these taxa to survive and prosper in these unique geochemical niches. This study provides fundamental understandings of the adaptive strategies of microorganisms in response to the strong environmental perturbation by alkali tailings. It also contributes to a better comprehension of how to remediate environments affected by alkaline industrial material.

Metamaterial-Based Analog Recurrent Neural Network Toward Machine Intelligence

Wave-based analog computation platforms hold the promise of realizing intelligent information processing with high speed and low computational cost, but current design principles face intractable problems in processing low-frequency wave information end to end at the physical layer. Here we theoretically demonstrate a concept of a metamaterial-based analog recurrent neural network (Meta-RNN) for intelligent classification of physical information carried by mechanical vibrations. With the spatiotemporal recurrence relation induced by coupled local resonators of the simulated metamaterial model, the Meta-RNN is capable of memorizing the internal hidden state in the dynamic displacement field. The trained coupling and synergy of local resonators lead to desirable vibration energy localization with selective frequency extraction capability, which can distinguish the intrinsic characteristics of vibration information. The proposed Meta-RNN provides a foundation for implementing a promising mechanical analog processor for intelligent vibration information processing and classification, and paves the way to efficient machine learning platforms for machine intelligence.

Exploiting the PIR Sensor Analog Behavior as Thermoreceptor: Movement Direction Classification Based on Spiking Neurons.

Pyroelectric infrared sensors (PIR) are widely used as infrared (IR) detectors due to their basic implementation, low cost, low power, and performance. Combined with a Fresnel lens, they can be used as a binary detector in applications of presence and motion control. Furthermore, due to their features, they can be used in autonomous intelligent devices or included in robotics applications or sensor networks. In this work, two neural processing architectures are presented: (1) an analog processing approach to achieve the behavior of a presynaptic neuron from a PIR sensor. An analog circuit similar to the leaky integrate and fire model is implemented to be able to generate spiking rates proportional to the IR stimuli received at a PIR sensor. (2) An embedded postsynaptic neuron where a spiking neural network matrix together with an algorithm based on digital processing techniques is introduced. This structure allows connecting a set of sensors to the post-synaptic circuit emulating an optic nerve. As a case study, the entire neural processing approach presented in this paper is applied to optical flow detection considering a four-PIR array as input. The results validate both the spiking approach for an analog sensor presented and the ability to retrieve the analog information sent as spike trains in a simulated optic nerve.

Proses Analogi Siswa Sekolah Dasar dalam Mengajukan Masalah Luas Daerah

This study analyzes the analogy process when elementary school students in pose area problems. This research used a qualitative method with a case study approach. The participants in this study were fifth-grade students of SD Negeri 1 Krembung, totaling 53 students. The selection of participants was made purposively. Data were collected using tests, interviews, and observations. Data analysis techniques used data reduction, data presentation, and conclusion drawing. Indicators of analogy process assessment based on Gentner Forbus's theory are retrieval, mapping, abstraction, representation, and evaluation. The results of this study indicate that elementary school students can use analogies in the learning process, but in the analogy process, there are differences between some students. The problems proposed by students are categorized as varied problems and complete processes, varied and incomplete processes, not varied and incomplete processes. In this study, it is suggested that novice elementary school students posing problems should use analogies as a reasoning process so that in posing new problems, they can come up with creative ideas.

Non-linear adaptive control inspired by neuromuscular systems

Current paradigms for neuromorphic computing focus on internal computing mechanisms, for instance using spiking-neuron models. In this study, we propose to exploit what is known about neuro-mechanical control, exploiting the mechanisms of neural ensembles and recruitment, combined with the use of second-order overdamped impulse responses corresponding to the mechanical twitches of muscle-fiber groups. Such systems may be used for controlling any analog process, by realizing three aspects: Timing, output quantity representation and wave-shape approximation. We present an electronic based model implementing a single motor unit for twitch generation. Such units can be used to construct random ensembles, separately for an agonist and antagonist ‘muscle’. Adaptivity is realized by assuming a multi-state memristive system for determining time constants in the circuit. Using SPICE-based simulations, several control tasks were implemented which involved timing, amplitude and wave shape: The inverted pendulum task, the ‘whack-a-mole’ task and a handwriting simulation. The proposed model can be used for both electric-to-electronic as well as electric-to-mechanical tasks. In particular, the ensemble-based approach and local adaptivity may be of use in future multi-fiber polymer or multi-actuator pneumatic artificial muscles, allowing for robust control under varying conditions and fatigue, as is the case in biological muscles.