This work presents the development and evaluation of a signal conversion and digitization subsystem for the DAPHNE testbench in the DUNE experiment. The main objective was to determine an optimal integration window size that ensures high frequency measurement accuracy and stability while minimizing FPGA computation time. Thirty window configurations were tested across short, intermediate, and maximum ranges, generating approximately 600,000 samples per configuration acquired via Jupyter.Results show that windows shorter than 10 μs exhibit significant dispersion due to instantaneous fluctuations, whereas windows larger than 60 μs stabilize the estimated frequency around the nominal value of 62.5 MHz with a maximum relative error below 0.02 %. Likewise, the relative uncertainty decreases exponentially with increasing window size, reaching below 500 ppm for windows of 60 μs or more, demonstrating the method's effectiveness as a digital integrator, where jitter reduction arises from statistical averaging over longer integration windows rather than from an explicit hardware or digital filtering stage. These findings define an optimal integration window range that ensures reliable and efficient measurements, contributing to the precise validation of DAPHNE electronic systems and supporting the preparation of DUNE subsystems.

Development of a PCB rotating coil system for small-aperture multipole magnets in Korea 4GSR project

Optimal identification of IIR-type fractional-order digital integrator and differentiator using a meta-heuristic optimization algorithm

The study examines how strategic positioning shapes the transformation of engineering companies’ business models in a digitally enabled, project‑intensive, B2B environment. Purpose of the study — to substantiate and systematize the conceptual foundations and mechanisms through which shifts in market positioning catalyze changes in value creation, delivery, and capture. The research integrates classic strategy and resource‑based views with business‑model theory and service‑dominant logic. Methods include a systematic literature review; comparative and content analysis of standards (ISO 9001, ISO 19650) and policies (CSRD/ESG); case‑based reasoning and benchmarking of digital practices (BIM, IoT, AI, cloud collaboration, digital twins); and mapping effects of repositioning onto the Business Model Canvas and strategy maps. The paper identifies four positioning types: technical‑technological, service‑oriented, data‑driven (digital), and ecosystem‑orchestrator and demonstrates their distinctive implications for customer segments and channels, value propositions, key resources/activities/partnerships, cost structures, and revenue logics (subscriptions, outcome‑based contracts, data monetization). It proposes a diagnostic matrix of external and internal determinants (technological, market, institutional, organizational) and a KPI framework for monitoring transition pathways and digital maturity. The results offer managers a road map for moving from a traditional contractor role toward a digital integrator and ecosystem coordinator, improving tender competitiveness, reducing coordination costs, and increasing lifetime customer value. The study operationalizes the link between external market identity (positioning) and internal business‑model architecture for engineering firms, embedding dynamic capabilities and ecosystem orchestration practices. As a result, strategic positioning functions as a systemic governance mechanism for business‑model evolution, enabling resilient growth under digital, regulatory, and sustainability pressures and providing a basis for further empirical testing and cross‑industry generalization.

In this work, the dynamic magnetization measurement system for characterizing the soft magnetic core materials of a fluxgate sensor is investigated. The alternating magnetizing field is generated by a solenoid coil. The reduction in field strength caused by the inductive reactance is overcome by cascading a proper metal film capacitor to the magnetizing coil to form a tank circuit. The pickup coil, which consists of inversely connected sensing and reference solenoids, is mounted inside the magnetizing coil to null the background output. The output response of the sample is converted into the magnetization signal by using a digital or analog integrator. It is found that the magnetizing curve of a ferrite cylinder shows the frequency-independent apparent susceptibility, which can be used as the standard for calibrating the dynamic magnetization measurement system. Experimental results show that the conversion factor for magnetization measurement remains constant up to 5.1 kHz with a digital integrator. The magnetization curves are low hysteresis with a consistent apparent susceptibility for the amorphous samples up to kilohertz frequencies, while nickel and mu-metal samples are generally hysteretic in the dynamic magnetization process. The proposed system is valuable for exploring the dynamic magnetization response for a variety of soft magnetic materials to construct the numerical model.

Frequency responses are frequently referred to in the stability analysis of fractional order control systems. Frequency response-based methods have been introduced in the literature to reduce complex fractional order systems. However, the magnitude and phase response improvement is not handled by these techniques. The optimization methods are utilized to improve the approximation of fractional order filters in the desired frequency range. The article discusses the ideal Fractional-Order Butterworth Filter (FOBF) configuration by utilizing integer-order rational approximations to achieve a precise magnitude and phase response. Additionally, this study utilizes optimal FOBF magnitude and phase characteristics to minimize errors and expands the approximation bandwidth to cover multiple decades in both pass and stop bands. Optimized fractional order Butterworth filter designs have been implemented in biomedical signal processing, audio engineering, telecommunications, and control systems, enhancing performance in noise reduction and signal fidelity across these applications. It is essential to precisely determine these transfer functions regarding frequency and time responses. Therefore, there is room for further enhancements in these approximation methods to reduce errors and enhance the accuracy of real-world implementations. In pursuit of this goal, the study introduced a powerful metaheuristic optimization technique called Enhanced Colliding Bodies Optimization (ECBO), which not only showcases better precision in modelling but also exhibits a higher level of stability when compared to existing methods. This process guides all entities towards an optimal solution in each successive round, boosting the likelihood of finding a superior solution and thoroughly examining the full range of potential solutions. This technique better fits the BF filter function to a fractional-order continuous filter. The digital integrator is optimized in the frequency domain using the Coyote Optimization Algorithm (COA) because of its effectiveness, ease of use, and strength in tackling various complex optimization challenges. This optimizes the magnitude and phase reaction of the low-pass BF filter depending on the Minimum Square Error (MSE). Expanding the scope of the ECBO’s search range allows the enhanced filter to closely replicate the frequency behaviour of fractional order continuous filter functions.

This paper introduces a compact, high-resolution time-to-digital converter (TDC) for lidar applications. In contrast to a conventional histogram-based peak detection method, this work proposes a mean detection method using a highly digitized phase-domain delta-sigma (PDΣ) TDC. The proposed TDC operates in an incremental Σ manner for a compact implementation and utilizing a digital integrator as a loop filter that facilitates an extended counting, resulting in significantly improved resolution. By utilizing a dual gated-ring oscillator (GRO) structure, time-quantization noise due to a residue phase of GRO is effectively mitigated. To address the issue of single-photon avalanche diode (SPAD) signals due to their stochastic nature, a dual time window is proposed to compensate for counting error when SPAD trigger missing occurs. Fabricated in a 65nm CMOS process, the prototype TDC occupies only an area of 2000μ2. It achieves a noise level of 27.6ps for the number of cycles of 32. When the cycle is 1000, it achieves a maximum integral non-linearity (INL) of 80ps (+53ps/-27ps) with a resolution of 8.5ps.

Digital business model transformation (DBMT) necessitates new managerial capabilities, yet the existing literature lacks an empirical understanding of managerial capabilities as antecedents to strategic change and firm performance. This paper builds on dynamic managerial capabilities theory to argue that managerial human capital—composed of leadership and entrepreneurial skills—is a critical facilitator of DBMT and resultant firm performance. Further, the research model proposes that managers' social capital and cognition positively moderate the relationship between human capital and DBMT. The study's findings from a sample of German Industry 4.0 firms provide new insights into the significance of managerial capabilities in a digital economy. This study advances management literature by demonstrating that the benefits of managers' human capital for DBMT are contingent on its form: entrepreneurial skills facilitate digital transformation integral for firm performance, while leadership skills have no impact on firm performance—neither directly nor indirectly through DBMT. Thus, this study provides strong evidence of the importance of entrepreneurial skills in driving DBMT to increase firm performance. Further, the findings offer a nuanced account of the interrelationships between dynamic managerial capabilities, revealing that higher levels of social capital and lower levels of cognition increase the positive effect of entrepreneurial skills on DBMT. This study altogether reaffirms the significance of managers' dynamic capabilities for strategic change enabled by DBMT and their performance benefits, yet it reveals that the effect mechanisms differ from those found in nondigital research settings.

This article presents a duty-cycled integrated-fluxgate (IFG) magnetic-to-digital converter for contactless current sensing. While previous works have proven high linearity, low noise, and low offset capabilities of fluxgate sensing, this work focuses on low energy operation. The mixed-signal front-end design enables energy-efficient duty cycling with a 13-bit digital integrator to retain the last converged output during sleep mode and resume searching in its vicinity upon wake up. The system achieves a ±2.4 mT measured range of magnetic fields for indirect current measurement. The hierarchical search modes achieve <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10\times $ </tex-math></inline-formula> faster convergence than analog implementations. The faster readout with a peak sampling rate of 770 kS/s translates to lower compensation energy per sample. The 3-dB bandwidth of 125 kHz is 67% higher than prior IFG art, with competitive 500-nT rms noise. The test chip fabricated in 250-nm CMOS technology consumes the lowest power of known IFG works. It can be duty-cycled to save energy in low-bandwidth applications or run at peak bandwidth for low latency.

Vibration signal analysis is the most common technique used for mechanical vibration monitoring. By using vibration sensors, the fault prognosis of rotating machinery provides a way to detect possible machine damage at an early stage and prevent property losses by taking appropriate measures. We first propose a digital integrator in frequency domain by combining fast Fourier transform with digital filtering. The velocity and displacement signals are, respectively, obtained from an acceleration signal by means of two digital integrators. We then propose a fast method for the calculation of the envelope spectra and instantaneous frequency by using the spectral properties of the signals. Cepstrum is also introduced in order to detect the unidentifiable periodic signal in the power spectrum. Further, a fault prognosis algorithm is presented by exploiting these spectral analyses. Finally, we design and implement a visualized real-time vibration analyzer on a Raspberry Pi embedded system, where our fault prognosis algorithm is the core algorithm. The real-time signals of acceleration, velocity, displacement of vibration, as well as their corresponding spectra and statistics, are visualized. The developed fault prognosis system has been successfully deployed in a water company.

Design of full-band infinite impulse response (IIR) digital differentiator (DD) and digital integrator (DI) based on the L_k-norm and the min-max optimality criteria have been demonstrated in literature. However, the designed IIR DDs and DIs using these criteria do not have linear phase or have unsatisfactory magnitude response. In this paper, a novel approach to design, optimize and improve the magnitude response and the linearity of the phase response of IIR DD and DI using the cuckoo search (CS) optimization algorithm is proposed. The proposed approach is based on a varied L_<i>k</i>-norm where <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> linearly increases with the number of the frequency samples between the values 1 and 2. The design and optimization of DDs and DIs are carried out using the CS optimization method due to its simplicity, efficiency, and robustness in solving general multidimensional optimization problems. The performance of the designed DDs and DIs using the proposed approach is compared with designs based on different criteria and algorithms available in literature. The comparison shows that the designed DDs and DIs based on the proposed approach have better phase responses and better or at least comparable magnitude responses compared to those of DDs and DIs designed using other methods in the literature.

Transient magnetic field sensors are used in various electromagnetic environment measurement scenarios. In this paper, a novel magnetic field sensor based on a digital integrator was developed. The antenna was a small B-DOT loop. It was designed optimally for the simulation. The magnetic field signal was digitally integrated with the improved Al-Alaoui algorithm, resulting in less integration error. To compensate for the bandwidth loss of the optical fiber system, we specially designed an FIR (finite impulse response) filter for frequency compensation. The circuit was described, and the transimpedance amplifier was specially designed to ensure the low noise characteristic of the receiver. The sensitivity of the sensor was calibrated at 68.2 A·m−1/mV, the dynamic range was 50 dB (1–300 kA/m), the linear correlation coefficient was 0.96, and the bandwidth was greater than 100 MHz. It was tested and verified under the action of an A-type lightning current. The sensor exhibited high-precision performance and flat amplitude-frequency characteristics. Therefore, it is suitable for lightning positioning, partial discharge testing, electromagnetic compatibility management, and other applications.

Fast lock-in amplifier electrochemical impedance spectroscopy for big capacity lead-acid battery

A cab seat suspension with a magneto-rheological (MR) fluid damper is introduced in this paper. A unified-format model for the MR damper is proposed to describe the dynamic characteristics of the MR damper. Also, a simple force-inverse model and a viscous damping tracking model are used for the coil current solution. A digital integrator and an extended Kalman filter are respectively adopted to obtain the vibration velocity of the chair frame and the relative motion velocity of the MR damper piston. A new skyhook control base with viscous damping tracking is applied to the semi-active seat suspension. In the simulation, compared with passive seat suspension under different displacement excitation (2, 4, 6, 8 Hz-sine, and random), the acceleration root mean square of the seat suspension with the MR damper is reduced by 52.2%, 32.2%, 41.3%, 50.8%, and 34.6%, respectively. In the experiment, the acceleration root mean square is reduced by 11.2%, 41.2%, 45.8%, and 31.5%, respectively under different displacement excitation (2, 4, 6, and 8 Hz-sine).

A second-order multi-bit $$\Sigma \Delta $$ modulator facilitating the usage of a two-step flash analog-to-digital converter (ADC) as an internal quantizer is presented. A digital assisted low-resolution feedback digital-to-analog converter (DAC) is introduced containing digital sigma-delta modulators (DSDMs) to reduce the number of levels in the feedback DAC alleviating dynamic element matching requirements. Two-step flash ADC as an internal quantizer in a $$\Sigma \Delta $$ modulator provides higher resolution; however, the delay in the two-step ADC can introduce instability in the $$\Sigma \Delta $$ modulator loop. In the proposed architecture, the fast processing of the digital integrator of DSDM in the feedback path compensates the latency of the two-step flash ADC. Therefore, this architecture provides more than 6 bits of resolution in the internal quantizer. The implementation of an extra DSDM in the outermost feedback path relaxes the matching requirement of the analog and digital integrators. The effectiveness of the proposed structure is demonstrated by the study of nonlinearities of the analog integrators.

The jambolan as it is popularly known as Syzygium cumini (L.) Skeels, is of Indian origin. Studies in various areas require estimation of leaf area over the growing cycle. Leaf area is an important aspect in the analysis of photosynthetic efficiency of plants. The objective of the present study was to evaluate S. cumini leaf area determination methods based on measurements by caliper, leaf area integrator and previous image calibration in ImageJ Software, comparing both methodologies. The present study was developed at Mato Grosso State University Carlos Alberto Reys Maldonado - UNEMAT, Alta Floresta campus - MT. Fifty leaves were analyzed, which were numbered from 1-50 in length (C) and width (L) with the aid of a digital caliper and leaf area integrator (Leaf area integrator LI-COR 3100), for measuring leaf area (AF), after the sheets were scanned on an HP Photosmart C4680 flatbed scanner and processed using ImageJ software. Given the data found, it was found that the method used via digital imaging was accurate and showed a high correlation with manual measurement, indicating that the morphological characteristics of leaf area, length and width of Jambolão leaves can be estimated through analysis and analysis. Digital image processing.

This article presents a low-dropout regulator (LDO), with analog-proportional (AP) and digital integral (DI) controls. The design concerns are discussed at first, on how to improve the load transient response, enhance the power supply rejection (PSR), and reduce the limit cycle oscillation (LCO). For a good output dc accuracy, the DI section is implemented with shift-register-based coarse- and fine-tuning loops. Meanwhile, the AP section, based on a low-supply flipped-voltage follower (FVF), can respond fast to the load step and input supply ripple. A replica loop is used to define the steady-state output current of AP, allowing a sufficient dynamic swing against the supply ripple. To lower the load current range with no LCO, the AP section will output all the current at very light load. An error amplifier (EA) with moderate gain is added to improve the light-load output accuracy. This EA also improves the PSR by approximately 6 dB. Fabricated in a 65-nm CMOS process, a 65-mV undershoot is measured with a 0-10-mA load current step under 0.6-V supply voltage and 50-mV dropout. Due to the fast AP, a 5-MHz operation clock is applied to the digital section, reducing the overall quiescent current to 29 μA. A 0.37-ps figure of merit (FoM) is then achieved. A -22-dB PSR at 1 MHz is measured at 0.6-V supply, 100-mV dropout, and 10-mA load current.

In this essay, the authors will discuss the similarities and differences of knowledge management and librarianship. They will propose and articulate the emerging role of academic and research libraries as the integrators of digital knowledge and research methods among academic enterprises, a role which they believe will transform librarians to knowledge professionals. The authors will try to answer or stimulate further discussion of multi-dimensional and provocative questions such as: What are the critical differences between knowledge management and library and information science? Will emerging functions or services, such as digital scholarship centers and research data management practices, allow academic and research libraries to more fully perform the functions of knowledge management? Will libraries’ emerging role in the knowledge creation ecosystem help define their new value proposition, from a collection-centric to knowledge-centric service model? How should libraries position library-based digital scholarship centers to be digital integrators for enterprise-wide digital learning, research, and knowledge creation?

ABSTRACTIn this paper, a new design methodology is developed for the implementation of a second-order microwave integrator on microstrip circuit. Firstly, an existing digital first-order integrator with best magnitude and phase performance is adopted as a prototype to give digital second-order integrator transfer function. Then, by using the autoregressive process and a least mean square based error function, coefficients of the formulated second-order digital integrator are transformed into the impedance values of transmission line elements. Different sets of impedance values are obtained through the optimization process, and design with a highly accurate frequency response having maximum relative error value not more than 7.2% over the angular frequency range 0.18pi to 0.94pi is selected for implementation purpose. RT/Duroid 5880 is used to fabricate the proposed second-order microwave integrator design. Measured results for transmission coefficient S21(f) are found to follow theoretical values over the frequency range of 1.8 GHz to 8.6 GHz.

An adaptable and compact fast pulse sampling module was developed for the neutron–gamma discrimination. The developed module is well suited for low-cost and low-power consumption applications. It is based on the Domino Ring Sampler 4 (DRS4) chip, which offers fast sampling speeds up to 5.12 giga samples per second (GSPS) to digitize pulses from front-end detectors. The high-resolution GSPS data is useful for obtaining precise real-time neutron–gamma discrimination results directly in this module. In this study, we have implemented real-time data analysis in a field programmable gate array. Real-time data analysis involves two aspects: digital waveform integral and digital pulse shape discrimination (PSD). It can significantly reduce the system dead time and data rate processed offline. Plastic scintillators (EJ-299-33), which have proven capable of PSD, were adopted as neutron detectors in the experiments. A photomultiplier tube (PMT) (model #XP2020) was coupled to one end of a detector to collect the output light from it. The pulse output from the anode of the PMT was directly passed onto the fast sampling module. The fast pulse sampling module was operated at 1 GSPS and 2 GSPS in these experiments, and the AmBe-241 source was used to examine the neutron–gamma discrimination quality. The PSD results with different sampling rates and energy thresholds were evaluated. The figure of merit (FOM) was used to describe the neutron–gamma discrimination quality. The best FOM value of 0.91 was obtained at 2 GSPS and 1 GSPS sampling rates with an energy threshold of 1.5 MeVee (electron equivalent).