Hardware Approach Research Articles

МЕТОДИ ТА ЗАСОБИ ВЕРТИКАЛЬНО-ПАРАЛЕЛЬНОГО ПОШУКУ В МАСИВАХ МАКСИМАЛЬНИХ І МІНІМАЛЬНИХ ЧИСЕЛ

The current stage of development of information technology is characterized by the expansion of the applications, much of which is associated with the accumulation of large data sets and parallel data searching in real-time. Such applications include automated systems for multi-level control of technological processes and complex objects, where at the lower levels of such systems is the accumulation of large data sets and their processing in real time. The main source in these systems are different sensors and devices that generate telemetric data. That is why it is very crucial to preprocess this data in real-time for finding further issues. One of the optimal ways for implementing it, is to use hardware approach like programmable logic device (PLD) with FPGA type. For resolving this issue in the article were analyzed the recent research and publications and has shown that the disadvantage of existing methods and algorithms for finding the maximum and minimum numbers in one-dimensional and two-dimensional arrays is that they are not focused on hardware implementation by using PLD with FPGA type. It is shown that the development of high-speed hardware for finding maximum and minimum numbers in one-dimensional and two-dimensional arrays should be carried out with an integrated approach, which includes methods, algorithms, structures and modern LPD and should be based on the following principles: homogeneity and regularity of structure; localization and simplification of connections between elements; modularity of construction; pipeline and spatial parallelism of data processing; consistency of the intensity of the discharge of bit sections with the intensity of their processing in the device. The basic operations for the implementation of algorithms for vertical-parallel search of maximum and minimum numbers in one-dimensional and two-dimensional arrays are highlighted and it is shown that they are based on the same type of basic operations with local and regular connections. In the article was developed the method of vertical-parallel searching of maximum and minimum numbers in arrays, which due to parallel processing of the first bit of an array of numbers and parallel formation of control words provides reduction of search time, which is mainly determined by bit numbers. Improved vertical-parallel method of simultaneous search of maximum and minimum numbers in two-dimensional arrays, which due to the simultaneous processing of p one-dimensional arrays and the use of the displacement method reduces the search time by p times compared to the existing method. It is shown that the time of vertical-parallel search of maximum and minimum numbers in one-dimensional and two-dimensional arrays is determined by the bit size of numbers, not their numbers. It is determined that the use of a common bus for formatting of the i-th bit of the maximum (minimum) number and the parallel formation of control words provides an increasing in the processing frequency of bit slices of one-dimensional array. It is determined that the amount of FPGA hardware resources that required for implementation a device for vertical-parallel searching of maximum and minimum numbers in a one-dimensional array mainly depends on the size of the array of numbers, and search time on their bit size.

Design and Implement a Multicast Approach in P4 Hardware Switches Operating at The 100 Gbps Line Rate and Based on Unicast Routing Tables

Design and Implement a Multicast Approach in P4 Hardware Switches Operating at The 100 Gbps Line Rate and Based on Unicast Routing Tables

Ambient Intelligence System Enabling People With Blindness to Develop Electrotechnical Components and Their Drivers

Along with the development of new assistive technologies, including ambient intelligence (AmI) environments, new job opportunities are created for people with blindness or visual impairment. Whereas research on software development for people with blindness has been conducted since the 1960s, the design and development of electrotechnical equipment still lacks any way to compensate for the disability which would enable people with blindness to perform even the activities pertaining to this field. This article aims to introduce these new technological procedures enabling the compensation of the disability of people with blindness when designing and developing electrotechnical components (or prototypes) and their drivers by using the AmI system RUDO modules and other tools. This includes the modules enabling measuring electrotechnical quantities, tracing of oscilloscope curves, and ensuring a unified user interface for programming and operation of the devices connected. Other approaches are introduced herein that focused on the production of mechanical components for device construction. This article also contains an illustrative video of practical use of these technological procedures by a person with blindness. To assess the usability of the designed technological procedures to the work of a designer with blindness and one without visual impairment, the cognitive walkthrough method was used. The main contribution of this article is to broaden the knowledge base by the principles of involving people with blindness in the development and construction of electrotechnical components (or prototypes). These new possibilities can be used practically, for instance, in computer education, which can offer new curricula for visually impaired students and focused on more practical issues where hardware and software approaches meet.

Cyber-Physical Systems using Open Design: an approach towards an Open Science Lab for Manufacturing

Cyber-Physical Systems (CPS) are fundamental in Industry 4.0 and manufacturing research communities, and research and technologies organizations (RTO) are keen to implement CPS laboratories. Due to the strong investment in these laboratories, it is unfordable the investment in CPS laboratories. This paper proposes a CPS architecture based on Open Design (an open-source approach for hardware and software), and the implementation of the laboratory created as an open-source and truly low-cost solution, designated as Open Science Lab for Manufacturing (OSLab4Man), addressing the reproducibility and replicability (R&R) practices for manufacturing research laboratories. An open-source and truly low-cost solution of the OSLab4Man and the bill of materials (BOM) of the physical components and some alternative components open-source and/or low-cost is presented, that enables a ubiquitous manufacturing system.

A Metaverse: Taxonomy, Components, Applications, and Open Challenges

Unlike previous studies on the Metaverse based on Second Life, the current Metaverse is based on the social value of Generation Z that online and offline selves are not different. With the technological development of deep learning-based high-precision recognition models and natural generation models, Metaverse is being strengthened with various factors, from mobile-based always-on access to connectivity with reality using virtual currency. The integration of enhanced social activities and neural-net methods requires a new definition of Metaverse suitable for the present, different from the previous Metaverse. This paper divides the concepts and essential techniques necessary for realizing the Metaverse into three components (i.e., hardware, software, and contents) and three approaches (i.e., user interaction, implementation, and application) rather than marketing or hardware approach to conduct a comprehensive analysis. Furthermore, we describe essential methods based on three components and techniques to Metaverse’s representative Ready Player One, Roblox, and Facebook research in the domain of films, games, and studies. Finally, we summarize the limitations and directions for implementing the immersive Metaverse as social influences, constraints, and open challenges.

A Digital Realization of Neuroglial Interaction Model and Its Network Structure

Astrocyte cells, the most existing abundant cells in central nervous system, play an essential role in modulating the neuronal activities, information processing, and regulating the synaptic plasticity through calcium (Ca2+) fluctuations of ions hemostasis by using a feedback mechanism. The pathophysiological and hypersynchronous neuronal activity can lead to the epileptic seizures, which is known as one of the neurodegenerative disorders in the field of neuroscience. This paper presents a modified neuron-astrocyte interaction (tripartite synapse) model based on leaky and integrate fire neuron and the astrocyte-synapse models using an area-efficient hardware approach called stochastic computing paradigm. The proposed model is synthesized physically on field-programmable gate array as a proof of concept. The implementation results of the presented model can mimic the bidirectional communication in biological minimal network of pre-postsynaptic and Ca2+-based model for astrocyte with considerably lower hardware cost. The influence of astrocytes on neural network behavioral has been investigated by providing a proper feedback mechanism and considering the role of gap junction coupling and the various coefficients on desynchronizing the impaired synchronization of the coupled neurons.

A Review of Intelligent Sensor-Based Systems for Pressure Ulcer Prevention

Pressure ulcers are a critical issue not only for patients, decreasing their quality of life, but also for healthcare professionals, contributing to burnout from continuous monitoring, with a consequent increase in healthcare costs. Due to the relevance of this problem, many hardware and software approaches have been proposed to ameliorate some aspects of pressure ulcer prevention and monitoring. In this article, we focus on reviewing solutions that use sensor-based data, possibly in combination with other intrinsic or extrinsic information, processed by some form of intelligent algorithm, to provide healthcare professionals with knowledge that improves the decision-making process when dealing with a patient at risk of developing pressure ulcers. We used a systematic approach to select 21 studies that were thoroughly reviewed and summarized, considering which sensors and algorithms were used, the most relevant data features, the recommendations provided, and the results obtained after deployment. This review allowed us not only to describe the state of the art regarding the previous items, but also to identify the three main stages where intelligent algorithms can bring meaningful improvement to pressure ulcer prevention and mitigation. Finally, as a result of this review and following discussion, we drew guidelines for a general architecture of an intelligent pressure ulcer prevention system.

Augmented Reality in Precision Farming: Concepts and Applications

The amount of arable land is limited, yet the demand for agricultural food products is increasing. This issue has led to the notion of precision farming, where smart city-based technologies (e.g., Internet of Things, digital twins, artificial intelligence) are employed in combination to cater for increased production with fewer resources. Widely used in manufacturing, augmented reality has demonstrated impactful solutions for information communication, remote monitoring and increased interaction. Yet, the technology has only recently begun to find a footing alongside precision farming solutions, despite the many benefits possible to farmers through augmenting the physical world with digital objects. Therefore, this article reflects on literature discussing current applied solutions within agriculture, where augmented realty has demonstrated a significant impact for monitoring and production. The findings discuss that augmented reality must be coupled with other technologies (e.g., simultaneous localization and mapping algorithms, global positioning systems, and sensors), specifically 9 are identified across 2 application domains (livestock and crop farming) to be beneficial. Attention is also provided on how augmented reality should be employed within agriculture, where related-work examples are drawn from in order to discuss suitable hardware approaches and constraints (e.g., mobility).

Modeling of hybrid active power filter using artificial intelligence controller: hardware and software prospective

<span lang="EN-US">The power factor is a significant concern in power systems. The significant power loss occurred due to electronic and electrical equipment damages affected by the deviation of physical characteristics, including voltage, current, and frequency parameters.The power loss and quality issues were resolved by introducing filtering techniques in electronic and electrical equipment. Many filtering techniques include passive filtering (PF), Active power filter (APF), and many hybrid approaches are already available. Most of these methods use proper compensation controlling approaches and failed to minimize the total harmonic distortion (THD), and harmonic mitigation in power systems has its best. In this article, an efficient Hybrid-APF using Artificial-Neuro Fuzzy interface system (ANFIS) for software and hardware perspective is designed. The proposed approach uses hybrid controlling strategies which include PI with artificial intelligence (ANFIS) controller, to control the power losses for H-APF. Additionally, current compensation is achieved by PQ-theory, followed by Hysteresis-Current- Controller (HCC). The hardware architecture of ANFIS with HCC is designed to improve the chip-area for real-time power applications.The present work analyzed by simulating the voltage and current waveform. The proposed-H-APF using ANFIS controller, both software and hardware approaches, is compared with other control techniques like H-APF with PI and Fuzzy logic controller by concerning THD,Reactive power, and Different Harmonics and loads improvements.</span>

A Survey on the Optimization of Neural Network Accelerators for Micro-AI On-Device Inference

Deep neural networks (DNNs) are being prototyped for a variety of artificial intelligence (AI) tasks including computer vision, data analytics, robotics, etc. The efficacy of DNNs coincides with the fact that they can provide state-of-the-art inference accuracy for these applications. However, this advantage comes from the high computational complexity of the DNNs in use. Hence, it is becoming increasingly important to scale these DNNs so that they can fit on resource-constrained hardware and edge devices. The main goal is to allow efficient processing of the DNNs on low-power micro-AI platforms without compromising hardware resources and accuracy. In this work, we aim to provide a comprehensive survey about the recent developments in the domain of energy-efficient deployment of DNNs on micro-AI platforms. To this extent, we look at different neural architecture search strategies as part of micro-AI model design, provide extensive details about model compression and quantization strategies in practice, and finally elaborate on the current hardware approaches towards efficient deployment of the micro-AI models on hardware. The main takeaways for a reader from this article will be understanding of different search spaces to pinpoint the best micro-AI model configuration, ability to interpret different quantization and sparsification techniques, and the realization of the micro-AI models on resource-constrained hardware and different design considerations associated with it.

High performance and energy efficient sobel edge detection

Sobel edge detection is widely used in computer vision and image processing but its processing time becomes a serious problem in real-time environments, especially when an image is very large. Instead of utilizing a hardware-accelerated approach, we propose a purely software-based method which is simpler and cheaper. Our algorithm reduces the number of arithmetic operations and data loads, so that processing speed is increased and energy consumption reduced. The processing time is further reduced by the use of AVX intrinsics and OpenMP directives which distribute the workload among the AVX engines in a multi-core architecture. Our algorithm reduces the number of arithmetic operations by 22.73% compared to that of the state-of-the-art Sobel (SOAS) algorithm, while the number of data loads are reduced by 43.75% compared to SOAS. Performance and energy consumption comparisons between our algorithm and SOAS, as well as with the Sobel functions offered by the OpenCV and IPP libraries are investigated, and the results demonstrate that a multi-core version of our algorithm, implemented by AVX intrinsics, is on average 3.20, 9.34, and 13.99 times faster than IPP, SOAS, and OpenCV respectively. Also, it consumes an average of 2.91, 8.43, and 11.21 times less energy than IPP, SOAS, and OpenCV. Our algorithm, utilizing software modifications alone, benefits from both shorter development time and reduced cost compared to hardware approaches relying on an FPGA, ASIC, or GPU, making it more suitable for resource-constrained environments.

Realization of fractional band pass filter on reconfigurable analog device

Abstract This paper presents a realization of fractional-order Band pass-filter (FOBF) based on the concepts of fractional order inductors and fractional order capacitors. The FOBF is designed and implemented using both simulation and hardware approaches. The proposed filter order is considered up to second order or less with any real positive number. One of the cases is considered when α ≤ 1 and β ≥ 1. In the second case, the filter is designed when β ≤ 1 and α ≥ 1. In order to calculate the optimal filter parameters, the modified Particle Swarm Optimization (mPSO) algorithm has been utilized for coefficient tuning. Also, a generalized approach to design any second order FOBF is discussed in this work. The realization and performance assessment have been carried out in simulation environment as well as in lab experiment with field programmable analog array (FPAA) development board. The experimental results indicate the value of efforts to realize the fractional filter.

Comparison of Failure Mode Inference Methods for Effective Failure Mode and Effects Analysis (FMEA) Implementation

Purpose: Omitting potential failure modes or inferencing inappropriate failure modes during failure mode and effects analysis (FMEA) implementation can lead to a lack of understanding of the causes of failures incurred or might lead to introducing inappropriate improvements. Therefore, it is critical to accurately infer the failure modes, which, in turn, requires selecting a suitable failure mode inference method because the results of such methods generally vary depending on the purpose and context of FMEA implementation.<BR>Methods: In this study, the advantages and disadvantages of functional and hardware approaches were compared and analyzed by applying them in mechanical and circuit components with respect to the implementation of component FMEA.<BR>Results: It was observed that the hardware approach can be more desirable for identifying the causes and mechanism of failures to prevent omissions and address the failure modes. However, when it becomes difficult to represent failure modes based solely on physical aspects, the functional approach can be used simultaneously with the hardware approach.<BR>Conclusion: Based on the aforementioned comparison and analysis, guidelines for selecting an effective FMEA method for implementing FMEA in organizations have been presented. However, this study focused only on component FMEA and did not consider system FMEA. Thus, the procedure for system FMEA, in terms of FMEA objectives and implementation, should also be examined.

Hardware implementation of metaheuristics through LabVIEW FPGA

Metaheuristic optimization methods have been implemented for solving several problems. However, when it is required to implement those algorithms in hardware to run online, there is not enough information. This paper describes how could be programmed and implemented those optimization algorithms. Moreover, a complete evaluation is shown as well as a comparative study regarding the most important metaheuristic optimization algorithms. Thus, this paper presents a comparison between five optimization algorithms implemented into a cRIO field-programmable gate array (LabVIEW FPGA) NI-9030 of National InstrumentsTM(NI). The algorithms implemented were particle swarm optimization (PSO), bat algorithm (BA), grey wolf optimizer (GWO), earthquake algorithm (EA), and Nelder–Mead algorithm (NM). To analyze hardware device utilization and execution time by each algorithm, synthesis results were presented. In addition, a set of ten benchmark functions was selected to compare performance between algorithms. Results show the feasibility of this approach for NI FPGA hardware. From device utilization results, GWO presents the lowest placed usage (29%) while NM shows the fastest execution time (0.683 ms). Nevertheless, PSO, GWO and EA show better performance between benchmark functions due their exploration characteristics which make possible to find a better solution.

Editorial to Special Issue “Remote Sensing Data Compression”

A huge amount of remote sensing data is acquired each day, which is transferred to image processing centers and/or to customers. Due to different limitations, compression has to be applied on-board and/or on-the-ground. This Special Issue collects 15 papers dealing with remote sensing data compression, introducing solutions for both lossless and lossy compression, analyzing the impact of compression on different processes, investigating the suitability of neural networks for compression, and researching on low complexity hardware and software approaches to deliver competitive coding performance.

Application of quantum machine learning using the quantum kernel algorithm on high energy physics analysis at the LHC

Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups. In this study, we employ a support vector machine with a quantum kernel estimator (QSVM-Kernel method) to a recent LHC flagship physics analysis: $t\bar{t}H$ (Higgs boson production in association with a top quark pair). In our quantum simulation study using up to 20 qubits and up to 50000 events, the QSVM-Kernel method performs as well as its classical counterparts in three different platforms from Google Tensorflow Quantum, IBM Quantum and Amazon Braket. Additionally, using 15 qubits and 100 events, the application of the QSVM-Kernel method on the IBM superconducting quantum hardware approaches the performance of a noiseless quantum simulator. Our study confirms that the QSVM-Kernel method can use the large dimensionality of the quantum Hilbert space to replace the classical feature space in realistic physics datasets.

A power control approach for a biosensor battery-supercapacitor storage system

This Letter proposed a new hardware approach based on the design of an intelligent system to manage energy storage sources in order to improve the battery life span. It is dedicated for the biomedical low power devices and specially an implantable biosensor since it consumes only 1.5mW. It involves three types of digital circuits based on the CMOS transistor which are: voltage comparator, analogue switches and OOK MICS transmitter. The proposed circuit manages the system supply and especially the supercapacitor charging. It enables the supercapacitor to supply the biosensor for 15 hours per 24 hours which presents 62% of the initial supply system life span. This would therefore prolong the battery life span, avoid the risk of the thermal leakage which is dangerous for the human body, and solve the problems of deep discharge and the decay of the discharge voltage for the supercapacitor.

The rogue access point identification: a model and classification review

Most people around the world make use of public Wi-Fi hotspots, as their daily routine companion in communication. The access points (APs) of public Wi-Fi are easily deployed by anyone and everywhere, to provide hassle-free Internet connectivity. The availability of Wi-Fi increases the danger of adversaries, taking advantages of sniffing the sensitive data. One of the most serious security issues encountered by Wi-Fi users, is the presence of rogue access points (RAP). Several studies have been published regarding how to identify the RAP. Using systematic literature review, this research aims to explore the various methods on how to distinguish the AP, as a rogue or legitimate, based on the hardware and software approach model. In conclusion, all the classifications were summarized, and produced an alternative solution using beacon frame manipulation technique. Therefore, further research is needed to identify the RAP.

Modeling and hardware-in-the-loop system realization of electric machine drives — A review

This paper presents a state-of-the-art review in modeling approach of hardware in the loop simulation (HILS) realization of electric machine drives using commercial real time machines. HILS implementation using digital signal processors (DSPs) and field programmable gate array (FPGA) for electric machine drives has been investigated but those methods have drawbacks such as complexity in development and verification. Among various HILS implementation approaches, more efficient development and verification for electric machine drives can be achieved through use of commercial real time machines. As well as implementation of the HILS, accurate modeling of a control target system plays an important role. Therefore, modeling trend in electric machine drives for HILS implementation is needed to be reviewed. This paper provides a background of HILS and commercially available real time machines and characteristics of each real time machine are introduced. Also, recent trends and progress of permanent magnet synchronous machines (PMSMs) modeling are presented for providing more accurate HILS implementation approaches in this paper.

Low-Cost Open-Source Device to Measure Maximal Inspiratory and Expiratory Pressures.

The measurement of maximal inspiratory (MIP) and maximal expiratory (MEP) pressures is a widely used technique to non-invasively evaluate respiratory muscle strength in clinical practice. The commercial devices that perform this test range from whole body plethysmographs to portable spirometers, both expensive and include a wide range of other respiratory tests. Given that a portable, low-cost, and specific option for MIP and MEP measuring device is not currently available in the market. A high-performance and easy-to-build prototype has been developed and the detailed technical information to easily reproduce it is freely released. A novel device is based on an Arduino microcontroller with a digital display, an integrated pressure transducer, and three-dimensional (3D) printed enclosure (total retail cost €80). The validation of the device was performed by comparison with a laboratory reference setting, and results showed accuracy within ±1%. As the device design is available according to the open-source hardware approach, measuring MIP/MEP can greatly facilitate easily available point-of-care devices for the monitoring of patients and, most important, for making this lung function measurement tool affordable to users in low- and middle-income countries.