Hardware Changes Research Articles

Deep Integration Between Polarimetric Forward-Transmission Fiber-Optic Communication and Distributed Sensing Systems.

The structural health of fiber-optic communication networks has become increasingly important due to their widespread deployment and reliance in interconnected cities. We demonstrate a smart upgrade of a communication system employing a dual-polarization-state polarization shift keying (2-PolSK) modulation format to enable distributed vibration monitoring. Sensing can be conducted without hardware changes or occupying additional communication bandwidth. Experimental results demonstrate that forward transmission-based distributed vibration sensing can coexist with PolSK data transmission without significant deterioration in performance. This proof-of-concept study achieved a sensitivity of 0.4141 μV/με with a limit of detection (LoD) of 563 pε/Hz1/2@100 Hz. The single-span sensing distance can reach up to 121 km (no optical amplification) with a positioning accuracy as small as 874 m. The transmission rate is 300 Mb/s, the QdB is 16.78 dB, and the corresponding BER is 5.202 × 10-12. For demonstration purposes, the tested vibration frequency range is between 100 and 200 Hz.

Assessment of sealing systems impact on the vibration and environmental safety of rotary machines

Energy saving control algorithms of centrifugal fans/pumps are based on the use of the frequency-controlled induction motor drives and pressure or flow rate sensors, the costs of which are comparable to the cost of the fans/pumps for low-power applications. The paper develops a new and simple estimation approach of the pressure and flow rate, utilising the measured Root Mean Square (RMS) value of the stator current, estimated motor’s input active power, reference stator voltage frequency and feed-forward backpropagation artificial neural network. The error percentage for both flow rate and pressure in experimental and estimated data is within the range of ±5%, which conforms to the ISO 13348 standard. A test rig for the rapid control prototyping of the fan is designed, and necessary design and test procedures are developed. The estimation approach is verified experimentally and demonstrates better estimation accuracy compared to the existing and possible similar simple approaches. The developed algorithm can be easily embedded into the industrial variable frequency drives without any hardware changes.

Improved Flow Rate and Pressure ANN Estimators for a Centrifugal Fan with Induction Motor Drive

Energy saving control algorithms of centrifugal fans/pumps are based on the use of the frequency-controlled induction motor drives and pressure or flow rate sensors, the costs of which are comparable to the cost of the fans/pumps for low-power applications. The paper develops a new and simple estimation approach of the pressure and flow rate, utilising the measured Root Mean Square (RMS) value of the stator current, estimated motor’s input active power, reference stator voltage frequency and feed-forward backpropagation artificial neural network. The error percentage for both flow rate and pressure in experimental and estimated data is within the range of ±5%, which conforms to the ISO 13348 standard. A test rig for the rapid control prototyping of the fan is designed, and necessary design and test procedures are developed. The estimation approach is verified experimentally and demonstrates better estimation accuracy compared to the existing and possible similar simple approaches. The developed algorithm can be easily embedded into the industrial variable frequency drives without any hardware changes.

Deep Integration of Fiber-Optic Communication and Sensing Systems Using Forward-Transmission Distributed Vibration Sensing and on-off Keying.

The deep integration of communication and sensing technology in fiber-optic systems has been highly sought after in recent years, with the aim of rapid and cost-effective large-scale upgrading of existing communication cables in order to monitor ocean activities. As a proof-of-concept demonstration, a high-degree of compatibility was shown between forward-transmission distributed fiber-optic vibration sensing and an on-off keying (OOK)-based communication system. This type of deep integration allows distributed sensing to utilize the optical fiber communication cable, wavelength channel, optical signal and demodulation receiver. The addition of distributed sensing functionality does not have an impact on the communication performance, as sensing involves no hardware changes and does not occupy any bandwidth; instead, it non-intrusively analyzes inherent vibration-induced noise in the data transmitted. Likewise, the transmission of communication data does not affect the sensing performance. For data transmission, 150 Mb/s was demonstrated with a BER of 2.8 × 10-7 and a QdB of 14.1. For vibration sensing, the forward-transmission method offers distance, time, frequency, intensity and phase-resolved monitoring. The limit of detection (LoD) is 8.3 pε/Hz1/2 at 1 kHz. The single-span sensing distance is 101.3 km (no optical amplification), with a spatial resolution of 0.08 m, and positioning accuracy can be as low as 10.1 m. No data averaging was performed during signal processing. The vibration frequency range tested is 10-1000 Hz.

A case report of system configuration issue in medical imaging due to system upgrade- changes in hardware and software.

Although the rapid growth in the efficiency of medical imaging is undeniable, the expansion of health information technology (HIT) into medical imaging has not been as seamless or well-integrated as it was thought to be. The socio-technical complexities in medical imaging associated with HIT systems can cause risks to patient harm and inconvenience, both individually and collectively, often in new, unforeseen, and unexpected ways. This study reflects a retrospectively collected single incident report related to medical imaging HIT systems, aiming to develop a set of preventive and corrective strategies. A combination of multiple deductive approaches (existing frameworks), i.e., HIT Classification Systems and 18-step medical imaging process workflow and inductive method (content analysis), were used to analyze the incident. The incident was identified as a "system configuration"-related software issue, contributed by system upgrade- changes in hardware and software. The incident was determined to occur during steps 10-12, i.e., "study selection and retrieval," "calling up of patient's referral," and "image review and interpretation," causing severe disruptions in the clinical workflow for several weeks. We propose 16 preventive and corrective strategies grouped under four key areas based on the socio-technical aspects associated with HIT systems. The key areas are (i) preparation and integration for upgraded systems, (ii) training for medical imaging specialists, (iii) contingency planning/immediate backup system, and (iv) system design and configuration. These strategies are expected to help healthcare staff, analysts, reporters, researchers, and relevant stakeholders improve care delivery and patient safety in medical imaging in the context of any system upgrades.

Optimizing hydrogen spark-ignition engine performance and pollutants by combining VVT and EGR strategies through numerical simulation

Hydrogen combustion engines are considered one of the leading solutions for decarbonizing road transport, mainly due to the possibility of adapting current engines for hydrogen operation with minor changes. This research extensively analyzes the effect of combined EGR (exhaust gas recirculation) and VVT (variable valve timing) strategies on the performance and emissions of a commercial turbocharged SI engine fueled with hydrogen. To this end, a 1D model of the said engine, widely validated for gasoline operation, was adapted to simulate the engine's behavior with hydrogen. This adaptation involved hardware changes and the implementation of a predictive hydrogen combustion submodel, previously calibrated using experimental data from a single-cylinder engine of similar geometry. Firstly, 400 hydrogen engine simulations without EGR were conducted to optimize the VVT system for fuel efficiency over a wide operating range. A detailed explanation of the causality of varying valve overlap on pumping losses, in-cylinder gas composition, and combustion is provided from these simulations. Then, a series of EGR sweeps were simulated to study its impact on performance and NOx at various degrees of load; concluding that diluting with EGR, rather than air, leads to reduced NOx emissions in exchange for slightly increased fuel consumption.

Online condition monitoring for DC-link capacitors of three-level NPC converters using noninvasive signal injection

This paper introduces an online method for monitoring the health condition of the DC-link in three-level NPC converters. This method does not require hardware changes or modifications to the control algorithm. It involves injecting a zero-sequence signal, added to the system reference voltages to generate a neutral-point current injection. A square waveform with an interharmonic cycle frequency is used for the signal injection to minimize estimation errors caused by existing signals. This combined signal allows for the simultaneous estimation of the capacitor equivalent series resistance (ESR) and capacitance (C) at different frequency components using wavelet decomposition. Additionally, a balance between the magnitudes of the system reference voltage and the signal injection is established to prevent power quality issues. Besides, the capacitor parameters are estimated in the time-frequency domain, enabling tracking of capacitor degradation and wear-out failure. A comparison with a Fourier-based approach shows that this method provides highly accurate capacitor parameter estimation with less than 2% errors, instilling confidence in its results. Experimental results from a three-level NPC converter’s laboratory setup demonstrate the proposed method’s effectiveness.

Towards Truly Adaptive Byzantine Fault-Tolerant Consensus

To acheive maximum performance, Byzantine fault-tolerant (BFT) systems must be manually tuned when hardware, network, or workload properties change. This paper presents our vision for a reinforcement learning (RL) based Byzantine fault-tolerant (BFT) system that adjusts effectively in realtime to changing fault scenarios and workloads. We identify several variables that can impact the performance of a BFT protocol, and show how these variables can serve as features in an RL engine in order to choose the context-dependent bestperforming BFT protocol in real-time. We further outline a decentralized RL approach capable of tolerating adversarial data pollution, where nodes share local metering values and reach the same learning output by consensus.

Cool Classical EI - A New Standard in EI and Its Many Benefits.

GC-MS with Cold EI improves all of the central GC-MS performance aspects, but it is known mostly for its provision of enhanced molecular ions. This occasionally leads to the misconception that, like chemical ionization, Cold EI is a supplementary ion source to standard EI. However, Cold EI is a highly superior replacement ion source to standard EI. While Cold EI mass spectra are the most informative and fully compatible with mass spectral library (such as NIST) identification, in some cases, the Cold EI mass spectra with their enhanced molecular ions result in a "picture" that is not as one is used to seeing. In this paper, we describe the "Cool Classical EI" mode, which produces classical EI mass spectra like standard EI. The change of Cold EI into the Cool Classical EI mode is software-based, requires no hardware change, and can be achieved even during the analysis. Several mass spectra that were obtained in the Cool Classical EI mode are presented and compared with standard EI and Cold EI mass spectra. In this paper we further demonstrate and discuss several benefits that Cold EI brings that are retained while using Cool Classical EI, including (a) much faster speed of analysis, (b) uniform response, (c) extended range of compounds amenable for analysis, (d) improved sample identification, (e) elimination of ion source related peak tailing, (f) elimination of intraion-source degradation, and (g) better signal-to-noise ratio of the sample compounds.

The design of a sample rapid magnetic resonance imaging (MRI) acquisition protocol supporting assessment of multiple articular tissues and pathologies in knee osteoarthritis

ObjectiveThis expert opinion paper proposes a design for a state-of-the-art magnetic resonance image (MRI) acquisition protocol for knee osteoarthritis clinical trials in early and advanced disease. Semi-quantitative and quantitative imaging endpoints are supported, partly amendable to automated analysis. Several (peri-) articular tissues and pathologies are covered, including synovitis. MethodA PubMed literature search was conducted, with focus on the past 5 years. Further, osteoarthritis imaging experts provided input. Specific MRI sequences, orientations, spatial resolutions and parameter settings were identified to align with study goals. We strived for implementation on standard clinical scanner hardware, with a net acquisition time ≤30 ​min. ResultsShort- and long-term longitudinal MRIs should be obtained at ≥1.5T, if possible without hardware changes during the study. We suggest a series of gradient- and spin-echo-sequences, supporting MOAKS, quantitative analysis of cartilage morphology and T2, and non-contrast-enhanced depiction of synovitis. These sequences should be properly aligned and positioned using localizer images. One of the sequences may be repeated in each participant (re-test), optimally at baseline and follow-up, to estimate within-study precision. All images should be checked for quality and protocol-adherence as soon as possible after acquisition. Alternative approaches are suggested that expand on the structural endpoints presented. ConclusionsWe aim to bridge the gap between technical MRI acquisition guides and the wealth of imaging literature, proposing a balance between image acquisition efficiency (time), safety, and technical/methodological diversity. This approach may entertain scientific innovation on tissue structure and composition assessment in clinical trials on disease modification of knee osteoarthritis.

Assessing the Stability of Photon-Counting CT: Insights from a Two-Year Longitudinal Study.

Among the advancements in computed tomography (CT) technology, photon-counting computed tomography (PCCT) stands out as a significant innovation, providing superior spectral imaging capabilities while simultaneously reducing radiation exposure. Its long-term stability is important for clinical care, especially longitudinal studies, but is currently unknown. This study sets out to comprehensively analyze the long-term stability of a first-generation clinical PCCT scanner. Over a two-year period, from November 2021 to November 2023, we conducted weekly identical experiments utilizing the same multi-energy CT protocol. These experiments included various tissue-mimicking inserts to rigorously assess the stability of Hounsfield Units (HU) and image noise in Virtual Monochromatic Images (VMIs) and iodine density maps. Throughout this period, notable software and hardware modifications were meticulously recorded. Each week, VMIs and iodine density maps were reconstructed and analyzed to evaluate quantitative stability over time. Spectral results consistently demonstrated the quantitative stability of PCCT. VMIs exhibited stable HU values, such as variation in relative error for VMI 70 keV measuring 0.11% and 0.30% for single-source and dual-source modes, respectively. Similarly, noise levels remained stable with slight fluctuations linked to software changes for VMI 40 and 70 keV that corresponded to changes of 8 and 1 HU, respectively. Furthermore, iodine density quantification maintained stability and showed significant improvement with software and hardware changes, especially in dual-source mode with nominal errors decreasing from 1.44 to 0.03 mg/mL. This study provides the first long-term reproducibility assessment of quantitative PCCT imaging, highlighting its potential for the clinical arena. This study indicates its long-term utility in diagnostic radiology, especially for longitudinal studies.

Sensitive Discrete Frequency Mid-Infrared Absorption Spectroscopy Using Digitally Referenced Detection.

Broadly tunable mid-infrared (IR) lasers, including quantum cascade lasers (QCL), are an asset for vibrational spectroscopy wherein high-intensity, coherent illumination can target specific spectral bands for rapid, direct chemical detection with microscopic localization. These emerging spectrometers are capable of high measurement throughputs with large detector signals from the high-intensity lasers and fast detection speeds as short as a single laser pulse, challenging the decades old benchmarks of Fourier transform infrared spectroscopy. However, noise in QCL emissions limits the feasible acquisition time for high signal-to-noise ratio (SNR) data. Here, we present an implementation that is broadly compatible with many laser-based spectrometer and microscope designs to address these limitations by leveraging high-speed digitizers and dual detectors to digitally reference each pulse individually. Digitally referenced detection (DRD) is shown to improve measurement sensitivity, with broad spectral indifference, regardless of imbalance due to dissimilarities among system designs or component manufacturers. We incorporated DRD into existing instruments and demonstrated its generalizability: a spectrometer with a 10-fold reduction in spectral noise, a microscope with reduced pixel dwell times to as low as 1 pulse while maintaining SNR normally achieved when operating 8-fold slower, and finally, a spectrometer to measure vibrational circular dichroism (VCD) with a ∼ 4-fold reduction in scan times. The approach not only proves versatile and effective but can also be tailored for specific applications with minimal hardware changes, positioning it as a simple and promising module for spectrometer designs using lasers.

Hardware-hardened Sandbox Enclaves for Trusted Serverless Computing

In cloud-based serverless computing, an application consists of multiple functions provided by mutually distrusting parties. For secure serverless computing, the hardware-based trusted execution environment (TEE) can provide strong isolation among functions. However, not only protecting each function from the host OS and other functions, but also protecting the host system from the functions, is critical for the security of the cloud servers. Such an emerging trusted serverless computing poses new challenges: Each TEE must be isolated from the host system bi-directionally, and the system calls from it must be validated. In addition, the resource utilization of each TEE must be accountable in a mutually trusted way. However, the current TEE model cannot efficiently represent such trusted serverless applications. To overcome the lack of such hardware support, this article proposes an extended TEE model called Cloister , designed for trusted serverless computing. Cloister proposes four new key techniques. First, it extends the hardware-based memory isolation in SGX to confine a deployed function only within its TEE (enclave). Second, it proposes a trusted monitor enclave that filters and validates system calls from enclaves. Third, it provides a trusted resource accounting mechanism for enclaves that is agreeable to both service developers and cloud providers. Finally, Cloister accelerates enclave loading by redesigning its memory verification for fast function deployment. Using an emulated Intel SGX platform with the proposed extensions, this article shows that trusted serverless applications can be effectively supported with small changes in the SGX hardware.

Real-time stealth optical transmission via fast laser frequency dithering.

We report a real-time 150 kbps stealth transmission within public optical communication of 10 Gbps dual polarization QPSK. The stealth data is modulated onto the frequency tuning signals of a fast-tuning laser source in the transmitter, which causes slight frequency dithering for the transmitted optical signal. In the receiver, the stealth receiver recovers the stealth data from the estimated frequency offset by the QPSK DSP algorithm. The experiments show the stealth transmission has few impacts on the public channel over a 300 km distance. The proposed method is fully compatible with existing optical transmission systems, and the only hardware change is to upgrade the transmitter laser to support frequency tuning through an external analog port for receiving stealth signal. The proposed stealth scheme can combine with cryptographic protocols to improve the integrated security of the system, and can be used as signaling transport for low level network control to reduce the communication overhead.

FPGA Implementation of SPI Protocol

Field Programmable Gate Array (FPGA) are versatile devices that can be programmed to implement various digital circuits, including communication protocols like Serial Peripheral Interface (SPI). The Serial peripheral interface protocol is a synchronous serial communication interface that allows for full duplex communication between a master device and a multiple slave MOSI, MISO, SCLK, and SS. MOSI and MISO are data lines, while SCLK is the clock signal generated by the master to synchronize transfers. SS is used by the master to select individual slave devices. By implementing the SPI protocol in FPGA, to gain flexibility and customization, as FPGAs can be reprogrammed for different applications without the need for dedicated hardware changes. The FPGA implementation of the Serial Peripheral Interface (SPI) protocol involves a structured methodology. With the help of pipeline buffer and DAM technique power dissipation is performed effectively. Finally, integrate the FPGA SPI module into the larger system, ensuring seamless communication with other components or microcontrollers. This systematic approach ensures a reliable and tailored FPGA based SPI implementation.

ЦИФРОВА ТРАНСФОРМАЦІЯ БІЗНЕС-СТРУКТУР: СТРАТЕГІЧНІ ОРІЄНТИРИ В ЕПОХУ ІННОВАЦІЙ ТА ТЕХНОЛОГІЧНИХ ЗМІН

Digital transformation has become a crucial factor in achieving success in this age of innovation and dynamic technological change. The purpose of the study is to research the impact of digital transformation on the functioning of business structures, develop recommendations for optimizing strategic guidelines under the influence of large-scale digitalization processes in the economy, and reveal what strategic principles and approaches companies use to adapt to the digital environment. The following research methods were used in the article: generalization and synthesis during the study of the theoretical work of foreign and domestic scientists, statistical analysis, and case method - during the study of the market position of the Amazon organization and the processes of digital transformation in it. This study explores successful cases of digital transformation across various sectors of the economy, as well as strategic directions and recommendations for enterprises to adapt to the requirements of the digital age and maximize the benefits of innovative technologies. The article discusses the concept of digital transformation of business structures. It is noted that building a scalable infrastructure using cloud services and virtualization allows organizations to easily adapt to changes in technological requirements without significant upfront investment in hardware or infrastructure changes. The results obtained during the research contribute to a better understanding of the importance of digital transformation for modern businesses, and provide a basis for further research in this area. Using the Amazon business case as an example, several key strategic guidelines were identified that contribute to successful adaptation to the era of innovation and technological changes, in particular: customer orientation, platform strategy, implementation of artificial intelligence solutions to optimize management processes, flexibility and adaptability. By taking Amazon as an example, it has been proven that digital transformation allows business entities to significantly increase their competitiveness, optimize business processes, enter new markets, and create new sources of income.

Towards Full Stack Adaptivity in Permissioned Blockchains

This paper articulates our vision for a learning-based untrustworthy distributed database. We focus on permissioned blockchain systems as an emerging instance of untrustworthy distributed databases and argue that as novel smart contracts, modern hardware, and new cloud platforms arise, future-proof permissioned blockchain systems need to be designed with full-stack adaptivity in mind. At the application level, a future-proof system must adaptively learn the best-performing transaction processing paradigm and quickly adapt to new hardware and unanticipated workload changes on the fly. Likewise, the Byzantine consensus layer must dynamically adjust itself to the workloads, faulty conditions, and network configuration while maintaining compatibility with the transaction processing paradigm. At the infrastructure level, cloud providers must enable cross-layer adaptation, which identifies performance bottlenecks and possible attacks, and determines at runtime the degree of resource disaggregation that best meets application requirements. Within this vision of the future, our paper outlines several research challenges together with some preliminary approaches.

Turn-Down Capability of Ansaldo Energia's AE94.3A

Abstract At an ever-faster pace, market's requirements for operational flexibility and turn-down capabilities are fundamental for heavy-duty gas turbines. Gas turbine energy plants require the lowest minimum environmental load (MEL) for times when the power request is mainly covered by renewable sources and, however, need to promptly respond to green energy shortages. Ansaldo Energia has addressed such requirements overall its gas turbine portfolio, recently including GT26, as discussed in GT2021-59457. This paper addresses the MEL reduction for AE94.3A via a modular upgrade package intended for the 110+ units Service fleet. To accomplish that, several features were designed and tested including variable inlet guide vanes (VIGV) extra-closure, air bypass through compressor blow-off lines, and extended use of anti-ice air recirculation. None of these require major hardware changes but only upgrades within a normal service outage, together with minor control system adaptations. The wide-ranging technical challenges attached to the MEL reduction features are discussed. Validation on field via special instrumentation focused on compressor, secondary air system (SAS), and turbine for several engines is also presented. The achieved minimum environmental load reduction is shown and its potential discussed together with some features already in place, such as the use of CO catalyzer or the regulation of control valves put on external cooling lines. The readiness and performance level of this MEL upgrade package, already in operation on several power plants, is here demonstrated. This makes the AE94.3A gas turbine more flexible toward current and future market requirements.

3D Absolute pose estimation of a staircase cleaning robot utilizing staircase geometry and minimal low-cost sensors

Thanks to its shape-shifting abilities, the sTetris robot can climb stairs while performing the cleaning task. The sTetris robot’s overall system operation depends on localization and positioning data, which are essential for its goal of autonomously navigating multi-floor environments. The mobile robots designed to work indoors generally rely on external systems for localization information. Regretfully, this frequently requires additional hardware fixing or changes to the indoor working environment in order to achieve accurate three-dimensional (3D) position and orientation (pose) for successful operation of the mobile platform. Nonetheless, the robot can be localized on the staircase by utilizing the information of the staircase’s geometry measurements, which are known ahead of time. This article demonstrates how the known geometry of staircases and measurements from minimal number of sensors can be used to accomplish 3D pose of the robot. Experiments carried out on a real robot in an authentic indoors setting successfully demonstrate the effectiveness of the suggested approach.

A study on impacts of hardware changes on performance of different multithreading libraries based on Gem5

This paper presents a thorough investigation into the performance of various multithreading libraries on different hardware configurations utilizing gem5. The study compares the performance of commonly-used multithreading libraries, including OpenMP, Pthread, TBB, and Dlib, through several benchmarks representing distinct types of workloads. Key hardware factors that directly affect the performance of each library are identified and analyzed. The research findings provide valuable insights and recommendations for selecting an appropriate multithreading library for a given application and hardware platform. Results indicate that the performance of multithreading libraries is influenced by numerous hardware factors, such as L1 cache size, L1 cache associate, L1 cache replacement policy, number of threads, and memory type. The libraries respond differently to these factors, and the performance variability of each library depends on the nature of the workload. The study offers a detailed analysis and valuable insights into the effects of these hardware factors on each library. This study contributes by presenting a comprehensive comparison of several widely used multithreading libraries across numerous hardware configurations, identifying the key hardware factors that influence the performance of each library, and providing insights and recommendations for selecting an appropriate multithreading library for a given application and hardware platform. Ultimately, the study results can help software developers make informed decisions when selecting a multithreading library and optimizing performance for their applications.