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Hardware developers started experimenting with Scrum to accelerate their product development. However, it is not possible to implement Scrum in the same way as it was done for software systems, where the approach is already well established. One of the processes required in Scrum is the estimate of task efforts when creating a backlog for an Agile Sprint. This article presents a pilot validation experiment of a novel Agile framework for the development of hardware systems, including a parametric tool to estimate task effort in a more rigorous way than traditional confidence votes. This article presents the validation of electronic hardware design task estimation and overall project performance. The validation is performed through experimental work with teams of junior engineering students. The validation experiment showed an improvement from a minimum of eight to a maximum of eighteen percent when employing the presented tool during planning phases of the development.

With the wide application of electronic hardware in aircraft such as air-to-ground communication, satellite communication, positioning system and so on, aircraft hardware is facing great secure pressure. Focusing on the secure problem of aircraft hardware, this paper proposes a supervisory control architecture based on secure System-on-a-Chip (SoC) system. The proposed architecture is attack-immune and trustworthy, which can support trusted escrow application and Dynamic Integrity Measurement (DIM) without interference. This architecture is characterized by a Trusted Monitoring System (TMS) hardware isolated from the Main Processor System (MPS), a secure access channel from TMS to the running memory of the MPS, and the channel is unidirectional. Based on this architecture, the DIM program running on TMS is used to measure and call the Lightweight Measurement Agent (LMA) program running on MPS. By this method, the Operating System (OS) kernel, key software and data of the MPS can be dynamically measured without disturbance, which makes it difficult for adversaries to attack through software. Besides, this architecture has been fully verified on FPGA prototype system. Compared with the existing systems, our architecture achieves higher security and is more efficient on DIM, which can fully supervise the running of application and aircraft hardware OS.

As the internet-of-things (IoT) era begins, there is a significant need for low-cost access control schemes that allow humans to activate and maintain IoT systems.Traditional biometric access control systems remain, however, vulnerable to physical attacks resulting in template theft/privacy, illegal access, etc. This paper aimed to address this by expanding on a proposal called BLOcKeR, which combines biometrics with two recent advances in hardware security—physically unclonable functions (PUFs) and hardware obfuscation. Hardware obfuscation is a technique to protect electronic hardware against access control circumvention attacks through locking mechanisms. A PUF is incorporated to tie the biometrics of the owner to the system. Combining these advances with biometrics, BLOcKeR protects a biometric system from physical attacks by locking its functionality and aims at ensuring successful activation of the locked system unlike the authentication /matching in biometric systems. In addition, unlike various existing approaches, BLOcKeR does not store the raw biometric of users while providing irreversibility, unlinkability, and revocability to the templates. We present a security analysis and experiments with more than 45,000 attack variants to evaluate BLOcKeR’s security against unauthorized access.

Home security is very crucial, different ways of security system have been enhanced such as the use of alarms, monitoring system, through the interaction of electronic hardware, software and much more. This project involves SMS verification and voice message based door access system to detect intruders, trespassers, criminals or any form of criminal act. The project is to design and construct a door security alarm system based on SMS verification and voice recognition. The objectives of this project are as follows: To design a security system that would automatically control the operations of a door via voice command through android application development and via SMS verification using GSM module. To develop and implement a system that utilizes voice command and SMS verification technology for access. To provide perfect security for door access, this project made use of two different technologies viz SMS verification and voice recognition. The microcontroller continuously receives command from the GSM module and the android application which is connected through the Bluetooth module. It then takes decision on the basis of the command received. The system has been designed to work with GSM technology, which will generate a message, every time an intruder tries to get an unauthorized access to the house. There is a unique voice keyword that grants access to the door via Google’s open-source speech-to-text on the android application using HC-05 Bluetooth module is employed to serve as a wireless link between the android application and the door. Having designed the system and found it working properly according to its design, the aim of the project can be said to be achieved. Thus, Voice Recognition and SMS verification offers a better security than traditional methods of security.

Spiking neural networks (SNNs) have the potential to closely mimic the information processing of biological brains, by using massive neurons that are interconnected in a complex network. Recent researches have considered using electronic hardware circuits to SNN implementations to meet real-time processing requirements. Network-on-Chips (NoCs) have been widely used to develop such SNN circuits as their interconnections can offer stable interconnectivity for neuron communications with high throughput and real-time execution. However, its scalability is limited due to expensive and complex NoC routers which leads to high energy consumption and large area utilization. Therefore, a minimally buffered deflection router (MBDR) is proposed in this work to address the scalability challenge of the hardware SNNs. It employs a deflection router technique to remove most of the inter-buffers and other expensive components of the conventional routers. Moreover, a novel flow controller is developed in MBDR to further reduce power consumption. Compared to existing approaches, experimental results show that based on 90-nm CMOS technology the area and power consumption of the proposed router are reduced by ~ 86% and ~ 88%, respectively. In the meantime, system throughput is maintained at a high level.

With the fast expanding utilization of intensity electronic hardware, dynamic force factor adjustment (PFC) has gotten essential for some kinds of intensity supplies in the market today. Uninterruptible Power Supplies (UPS) are broadly used to convey solid and excellent capacity to basic burdens under all lattice conditions. This paper proposes a high-recurrence secluded UPS framework for low force applications. The proposed framework comprises of a solitary stage AC-DC converter, SEPIC DC-DC converter, and a battery. The single-stage AC-DC converter gives galvanic segregation, input power factor remedy, and constant conduction of both information and yields current. The low battery bank voltage is ventured up to high DC-interface voltage by utilizing a high voltage gain SEPIC converter. In this paper, UPS charging system with almost unity power factor is proposed. In conventional systems, the bridge rectifier and DC-DC converter are used in this system. Using this methodology, the power factor and harmonics are decreased. We use the bridgeless SEPIC converter for battery charging applications. This system can perform rectification and DC to DC conversion stages with improved power factor and low harmonics. Current control method (MOSFET) is used for control logic. Design of the converter is done in MATLAB and analysed the PI controller with optimized Kp, Ki using GA intelligent control method.

Many options exist for developing and implementing monitoring systems for research and scientific applications. Commercially, available systems and devices, however, are usually built using proprietary tools and programming instructions, and often offer limited flexibility for end users. The use of open-source hardware and software has been embraced by the research and scientific communities and can be used to target unique data and information requirements. Development based on the Arduino microcontroller project has resulted in many successful applications, and the Arduino hardware and software environment continues to expand and become more powerful but can be intimidating for users with limited electronics or programming experience. The open-source Python language has gained in popularity and is being taught in schools and universities as an introduction to computer programming and software development due to its simple structure, ease of use, and large standard library of functions. A project called CircuitPython was developed to extend the use of Python to programming hardware devices such as programmable microcontrollers and maintains much of the original Python language and features, with additional support for accessing and controlling microcontroller hardware. The objective of the work reported here is to discuss the CircuitPython programming language and demonstrate its use in the development of research and scientific applications. Several open-source sensing and monitoring systems developed using open-source hardware and the open-source CircuitPython programming language are presented and described.

Ocean acidification (OA) is the process whereby anthropogenic carbon dioxide is absorbed into seawater, resulting in altered carbonate chemistry and a decline in pH. OA will negatively impact numerous marine organisms, altering the structure and function of entire ecosystems. The progression of OA, while faster than has occurred in recent geological history, has been subtle and detection may be complicated by high variability in shallow-water environments. Nevertheless, comprehensive monitoring and characterization is important given the scale and severity of the problem. Presently, technologies used to measure OA in the field are costly and limited by their detection of only one carbonate chemistry parameter, such as pH. Discrete water samples, by contrast, offer a means of measuring multiple components of the carbonate system, including parameters of particular explanatory value (e.g., total alkalinity, dissolved inorganic carbon), for which field-based sensors do not presently exist. Here we describe the design, use, and performance of a low- cost (

The electric parking brake (EPB) system as the complex mechatronic system consists of the actuators that generate the clamping force necessary to hold the vehicle safe, the conventional calipers that convert clamp force into brake torque, electronic hardware with the Electronic Control Unit (ECU), cable harness and switches and especially the control software providing the functions that the driver will experience. Like most of the modern automotive components, the EPB is equipped with embedded electronic systems that include ECU, electronic sensors, signals, bus systems, and coding. Due to the complex application in electrical, electronics and programmable electronics, the need to carry out detailed safety analyses that are focused on the potential risk of malfunction is crucial for automotive systems. This paper describes a possible division of the EPB sub-functions between the supplier the wheel brakes and the supplier which supplying the ECU. Functional safety must be a guarantee with concerning the overall vehicle system. Functional safety is according to the requirements of the ISO 26262 standard and in the context of this paper relates solely to the E/E components (electrical and/or electronic) of the EPB. This paper covers the hazard analysis and risk assessment relevant to the EPB control software, and the derived allocation of ASIL risk levels to the EPB software elements of the functional architecture of the EPB.

Artificial neural networks have dramatically improved the performance of many machine-learning applications such as image recognition and natural language processing. However, the electronic hardware implementations of the above-mentioned tasks are facing performance ceiling because Moore’s Law is slowing down. In this article, we propose an optical neural network architecture based on optical scattering units to implement deep learning tasks with fast speed, low power consumption and small footprint. The optical scattering units allow light to scatter back and forward within a small region and can be optimized through an inverse design method. The optical scattering units can implement high-precision stochastic matrix multiplication with mean squared error 10 - 4 and a mere 4 × 4 μm2 footprint. Furthermore, an optical neural network framework based on optical scattering units is constructed by introducing “Kernel Matrix”, which can achieve 97.1% accuracy on the classic image classification dataset MNIST.

Background. Ecological pollution of Ukrainian Polyssia in result of Chornobyl disaster caused the necessity of public health monitoring at these territories. Development of medical information systems with databases and data protection were supposed to be the good tools for such monitoring organization. Materials and methods. A set of methods was used for the construction of networked, Internet-based medical information system with databases. Relational database technology was applied; used diagnostic information was in DICOM standard. Software C# and MySQL were used. For electronic hardware key ATmega8 microcontroller and the scheme that implements the USB interface were used. Results. Information system was designed for the monitoring in time the numbers of biochemical and other numerical indicators characterizing examined organism state of the person in conditions of territories of Ukrainian Polyssia that were ecologically polluted due to Chornobyl disaster. Developed system is networked, Internet-based; it contains a number of interconnected electronic databases with ordered data and appropriate output of this information on monitors, including biochemical laboratory data about the presence of environmental pollutants in organism. The possibility of preliminary automated data analysis as well as protection of personal data of patients, other surveyed persons was provided due to the development of original electronic hardware key. The information on the structure of developed system, its functions as well as functions of some of its most important blocks, samples of software developed by the authors and means of information protection in such system was given. Conclusion. Results of the development of new medical information system based on databases with for monitoring of numerical indicators of public health were presented. Data protection in this information system was realized using original electronic hardware key.

Recent efforts to improve the performance of bearingless motors have focused on “combined winding” machine designs that use the same coils for torque and suspension force production. While combined winding designs have been successful in increasing the machine performance, they add substantial cost and complexity to the power electronics required for the bearingless drive system. This article presents a bearingless drive concept, which eliminates the additional power electronic hardware requirements for a parallel combined winding design. The resulting drive requires the same hardware components as a traditional, separated winding bearingless motor. The article proposes and explains the design and theory of operation, proposes a simple control implementation, and presents initial validation via simulation results. The theory and design presented are valid for both conventional $p\pm 1$ bearingless motor designs (i.e., bearingless permanent magnet designs) as well as $p_s=1$ bearingless motor designs (i.e., bearingless ac homopolar designs). Experimental results are provided that validate the proposed concept and demonstrate stable levitation of a bearingless motor.

This paper presents a novel low-cost technique to measure the insertion force of a surgical needle on a testing surface to check needle strength. A combination of a load cell with a current sensor for a linear DC motor has been used to estimate the insertion force based on Kalman Filter (KF). The custom-designed and in-house fabricated system to estimate the insertion force comprises of the motor coupled with a vertically articulated arm. The needle to be tested is mounted at the end of the arm. Movement of the arm has been controlled electronically to produce the insertion force by the needle to a testing surface. The sensory measurement data generated during this process has been collected using Arduino based embedded electronic hardware. The KF based proposed strategy has been validated using the developed system by conducting various tests with different needles. Results in the form of penetration force and friction force have been experimentally observed and are then compared with standard force meters. Comparative analysis witnesses efficiency of the proposed approach.

The total economic cost of neurological disorders exceeds £100 billion per annum in the United Kingdom alone, yet pharmaceutical companies continue to cut investments due to failed clinical studies and risk [1]. These challenges motivate an alternative to solely pharmacological treatments. The emerging field of bioelectronics suggests a novel alternative to pharmaceutical intervention that uses electronic hardware to directly stimulate the nervous system with physiologically inspired electrical signals [2]. Given the processing capability of electronics and precise targeting of electrodes, the potential advantages of bioelectronics include specificity in the time, method, and location of treatment, with the ability to iteratively refine and update therapy algorithms in software [3]. A primary disadvantage of the current systems is invasiveness due to surgical implantation of the device.

In this paper, the impacts of various data integrity attacks on the power electronic hardware present in an EV charger are comprehensively analyzed in order to provide necessary recommendations to defend against cyberattacks on electric vehicles and their onboard charging (OBC) systems. The adverse scenarios arising due to cyberattacks are carefully reviewed in this study, which includes (a) interfering with the main charger controller (FPGA) logic and its data, (b) establishing fake communication between the charging controller and other electronic control units (ECUs) connected over same controller area network (CAN) bus, and (c) interfering with the battery management system functionalities. A 6.6kW interleaved totem-pole PFC front-end followed by a high frequency DC-DC converter is used as our OBC representative system in this analysis. Possibilities and ways of potential cyberattacks on this model are investigated in detail. Effort is made towards providing software as well as hardware design-level protection mechanisms to mitigate the malicious effects of such cyberattacks on the OBC hardware. This system is simulated in MATLAB/Simulink to verify the fault occurrences under various data integrity attacks as well as to validate the effectiveness of our proposed countermeasure approaches. Quantitative analyses of the obtained results clearly demonstrate that if adequate precautionary measures are properly taken while designing the charging architecture (e.g., implementing intelligence to the main controller), any electrical hazard or deterioration of health of the components can be avoided to the maximum extent under the circumstances of a malicious cyberattack.

It has long been known that photonic communication can alleviate the data movement bottlenecks that plague conventional microelectronic processors. More recently, there has also been interest in its capabilities to implement low precision linear operations, such as matrix multiplications, fast and efficiently. We characterize the performance of photonic and electronic hardware underlying neural network models using multiply-accumulate operations. First, we investigate the limits of analog electronic crossbar arrays and on-chip photonic linear computing systems. Photonic processors are shown to have advantages in the limit of large processor sizes ( ${>}\text{100}\; \mu$ m), large vector sizes ( $N > 500)$ , and low noise precision ( ${\leq} 4$ bits). We discuss several proposed tunable photonic MAC systems, and provide a concrete comparison between deep learning and photonic hardware using several empirically-validated device and system models. We show significant potential improvements over digital electronics in energy ( ${>}10^2$ ), speed ( ${>}10^3$ ), and compute density ( ${>}10^2$ ).

Maximizing profits while minimizing risk in a technologically advanced silicon industry has motivated the globalization of the fabrication process and electronic hardware supply chain. However, with the increasing magnitude of successful hardware attacks, the security of many hardware IPs has been compromised. Many existing security works have focused on resolving a single vulnerability while neglecting other threats. This motivated to propose a novel approach for securing hardware IPs during the fabrication process and supply chain via logic obfuscation by utilizing emerging spin-based devices. Our proposed dynamic obfuscation approach uses reconfigurable logic and interconnects blocks (RIL-Blocks), consisting of Magnetic Random Access Memory (MRAM)-based Look Up Tables and switch boxes flexibility and resiliency against state-of-the-art SAT-based attacks and power side-channel attacks while incurring a small overhead. The proposed Scan Enabled Obfuscation circuitry obfuscates the oracle circuit’s responses and further fortifies the logic and routing obfuscation provided by the RIL-Blocks, resembling a defense-in-depth approach. The empirical evaluation of security provided by the proposed RIL-Blocks on the ISCAS benchmark and common evaluation platform (CEP) circuit shows that resiliency comes with reduced overhead while providing resiliency to various hardware security threats.

Conducted Emissions (CE) contributes to a significant percentage of compliance failures in the verification stage of electronic hardware. In this work, the effect of cable-bend on the CE results is studied. The cable bend at the LISN-end can affect the common mode impedance due to the change in the mutual coupling between the cables. A full-system hybrid-solver capability is implemented based on the observations. The cable bend effect is demonstrated using the simulation setup comprising of LISN, cable harness and D UT. The effect is further validated using measurements.

The main needs of a vehicle trackers are security and logistical planning. The GPS (Global Positioning System) realtime location provides more security and can be useful for fleet management.Vehicle trackers become more and more useful not only for car fleet companies but also for personal use, improving safety by theft recovery. The development of this work proposes a low cost Internet of Things (IoT) system based on the ESP32 controller as electronic hardware, ProIoT company as IoT platform and long range wide area network as communication protocol.

We present here Terahertz (THz) near-field imaging results providing important supplementary information for the detection of counterfeit electronic hardware. By using near-field transceiver microprobes we are able to perform depth-resolved measurements at packaged integrated circuits below the diffraction limits of conventional THz far-field tools and without the draw-backs of ionizing x-ray imaging. The applied reflection-mode can be used e.g. for the inspection of multi-layer structures, the localization of deviations from standard structures and the investigation of samples on THz opaque substrates. In this work we show as an example the detection of hidden discrepancies between externally identical ICs.

Recent advancements in computational power technology and wide-usage of high qualified electronic hardware allow many engineers to create their control strategies in data-driven and model-free approaches, such as reinforcement-learning, genetic algorithm and other machine learning topics, rather than classical and modern control approaches. In this study, Q-Learning RL algorithm combined with analytic LMI method has been utilized to solve micro-scale vibration isolation problem as energy efficient as possible.

The evolving trend of the semiconductor supply chain resulted in a wide array of trust issues for electronic hardware. Among them, malicious alteration of designs in an untrusted design house or foundry, also known as hardware Trojan insertion, has emerged as a serious concern. A popular countermeasure against hardware Trojan attacks relies on identifying a Trojan fingerprint in a side - channel parameter. However, side - channel analysis suffers from (1) the process variations introduced in chips during fabrication and (2) the inability of conventional techniques to detect side - channel signatures of a small Trojan in a large design. In this paper, we propose a machine learning approach to detect malicious Trojan activities in a chip with high sensitivity. We use a custom - designed circuit board and measurements from several Trojan-inserted test chips for validating our proposed technique. We were able to detect Trojans with very high confidence and precision. Our method could detect extremely small Trojans of size as small as four gates with over 80% confidence. For larger Trojans, the prediction confidence is above 99%. We have also devised and implemented a framework for time - efficient automatic testing of a target chip using our method.

This paper analyzes the impacts of various data integrity based cyber attacks on power electronic hardware present in electric vehicle (EV) chargers and proposes an universally applicable hardware-based countermeasure algorithm to protect the onboard charging (OBC) systems. The effectiveness of the proposed defense mechanism is comprehensively analyzed by testing the system against several recurring cyberattack triggered faults in the OBC. To evaluate the impact of various cyberattacks on the system, two different power electronic topologies of EV OBC are taken into consideration. Further on, single phase and three phase charger topologies are simulated in MATLAB/Simulink to comprehend the impact of various faults occuring as a result of different data integrity attack scenarios, and to validate the effectiveness of the proposed algorithm. Quantitative analysis of the results demonstrates that the proposed intelligent data processing algorithm, implemented in the charger's main controller, can be effectively used with different charging architectures / topologies proving its universal application against cyberattacks on the OBC systems.

Analogue artificial neural networks are widely considered as promising computational models that more closely imitate the information processing capabilities of the human brain compared to digital neural networks. The significant computation power and the much reduced power consumption per operation make the analogue implementation of neural networks very attractive. There is an active research on artificial neural networks (ANNs) implementation using both analogue photonic and electronic hardware [1] – [4] . However, compared to digital realisations the conventional analogue systems are more sensitive to the noise that is inevitably present in practical implementations [2] , [3] . Noise properties in ANNs have been studied both in the electronic and photonic domains. However, photonic ANNs are much less investigated compared to the electronic implementations, for which some training techniques have been proposed to enhance ANNs robustness against noise [1] , [4] .

Telerobotics is the area of robotics concerned with the control of robots from a distance, mainly using wireless connections or the Internet. It is a combination of two major subfields, teleoperation and telepresence. The work presented in this chapter belongs to the field of teleoperated robots, where a remote centre sets commands to the robot and supervises the performed motion by receiving feedback from its sensors. In teleoperated robots the control algorithm can be balanced between the remote host and the local host in the robot, which yields to several kind of possible control schemas. The key components needed to develop telerobotics applications are the following: control (algorithm and real time implementation), sensors (world sensing and information processing) and wireless communication (generally using standard wireless technologies, i.e. IEEE 802.11) [Angelo, 2003], [Anvari, 2007], [Gumaste, 2007], [Mehani, 2007], [Chumsamutr, 2003], [Hespanha, 2007], [Bambang, 2007]. This chapter is outlined within both educational and research fields in telerobotics, and so its aim is to offer a reliable and low cost architecture to be implemented in research labs. The robotic platform consists of the Pioneer 3DX (P3-DX) from the company MobileRobots (see Figure 1). It is made of an aluminium body (44x38x22cm) with 16.5cm diameter drive wheels. The two DC motors use 38.3:1 gear ratios and contain 500-tick encoders. The differential drive platform is highly holonomic and can rotate in place moving both wheels, or it can swing around a stationery wheel in a circle of 32cm radius. A rear caster is included for balancing the robot. On flat floor, the P3-DX can move at speeds of 1.6 mps. At slower speeds it can carry payloads up to 23 kg. In addition to motor encoders, the P3DX base includes eight ultrasonic transducer (range-finding sonar) sensors arranged to provide 180degree forward coverage. This robot includes a 32-bit RISC-based controller, with 8 digital inputs and 8 digital outputs plus 1 dedicated A/D port; 4 of the outputs can be reconfigured to PWM outputs [P3-DX, 2009]. The P3-DX can be ordered with a complete electronic hardware [MobileRobots, 2009], which include wide range sensors, an on-board PC and Wireless Ethernet communication device. However, the authors propose to start from a basic structure that allows to be customized depending on the final application. This decision offers the opportunity of working with open platforms which is specially suitable for educational labs in engineering schools. On 1

Recent studies have shown that the electronic hardware devices can be compromised by the faults and fault tolerance is a crucial capability. This paper addresses the challenge of fault detection in the CMOS circuits, using two bio-inspired structures based on the HP lab's memristor and the BSIM3v3.2.2 transistor models. The first fault detection circuit (FDC) includes the memristor-based synapses and a modified leaky integrate-and-fire (LIF)-based neuron. The memristor-based synapse circuits can be further optimized which is the proposed second fault detection method (O-FDC), and it has a lower hardware overhead and power consumption compared to the former. Experimental results demonstrate that the proposed structures can detect the circuit faults under the inputs of direct current (DC), alternating current (AC) voltage sources, and pulse signals. Under the input of DC, the fault detection times for the two proposed structures are about 0.16 ms and 1.2 ms, respectively; when the input source is AC, the corresponding fault detection times are about 0.206 ms and 0.758 ms; and it takes only 6.47us for fault detection under the input of pulse signals. This work provides an alternative solution to enhance the fault-tolerant capability of the hardware systems.

Faults that occur during the transmission and distribution of energy usually occur in power transformers. The interruptions in the transformers, the voltage drops, the sudden interventions in the over currents cause important problems. For this reason, power transmission and distribution companies should perform routine tests and transformers more effectively. In this study, transformer routine tests have been analyzed by using the generated firefly algorithm. Data from sensor and measuring instruments in the transformer units obtained. A data collection system consisting of hardware and software has been created to collect the data and transfer it to the computer center. Electronic hardware has been utilized for transferring data from sensors connected to different units of transformer to computer. The data received from the transformer has been synchronized with the PIC microcontrollers in the designed circuit and transferred quickly and safely to the computer by means of the USB port. An interface written in Visual Studio programming language has been created in order to present the analog signals in digital format to the user in a visual way. The voltage values obtained from the sensors have been displayed on the Transformer Routine Test Analysis Program screen created on the computer. The measurement accuracy and success of the designed software and hardware have been tested on real system. The data obtained showed that the system is successful. Thus, remote monitoring, control and routine testing of transformers with the software and hardware created have been realized.

Modern variable-speed drives must be able to deal with ride-through faults with dips of 70–90% to ensure the continuity of the process without the energy store station discharge and carry out significant effects to its performance. So, the existent contingencies to such case are tripping-method from grid, robust DC-Link with higher capacitors and additional power electronic hardware. Nevertheless, they comprehend a common drawback for being costly in the industry. Therefore, the Power Loss Ride Through behaviour on variable-speed drives is an important feature which is a worst-case where the system can suffer dips near to 99% on grid. Recently, Modular Multilevel Cascade Converters have been applied in Variable-Speed Drives applications due to their capability to operate at high-power rates and features such as enhanced fault-ride through capability during critical dip voltage (e.g., 99% of amplitude) in grid. Therefore, this paper presents a control strategy based on a transition mechanism between outer control loops on the nested control of a Modular Multilevel Matrix Converter drive with the aim to improve the Power Loss Ride-Through performance through keeping the energy store station uniform and stable. Simulation results obtained using PLECS software are presented to validate the effectiveness of the proposed control strategy.

Using a typical Semiconductor Parameter Analyzer (SPA) for semiconductor reliability stress tests such as Time Dependent Dielectric Breakdown (TDDB), bias temperature instability (BTI), Hot Carrier Injection (HCI), has limitations. The SPA tends to be inflexible in dealing with concurrent multiple failure modes, managing multiple touchdown requirements, and so on. These issues can be effectively mitigated through the usage of massively parallel reliability tests. This paper presents a new Parallel Reliability Test Platform (PRTP) that has been developed and integrated at Intel Corp. with the support of Intel's test partners. The PRTP was built innovatively by integrating customized and modularized electronic hardware, new parallel probing solutions and in-house developed automation systems. It enables the capability to conduct measurements on multiple devices and/or multiple dies and demonstrates a multifold increase in throughput. This significant enhancement of industrial reliability testing throughput facilitates the collection of large data sets and sample sizes in realistic timeframes and enables Intel to release new products to the market in shorter time while maintaining robust statistical confidence.

Neural coupled oscillators are a useful building block in numerous models and applications. They were analyzed extensively in theoretical studies and more recently in biologically realistic simulations of spiking neural networks. The advent of mixed-signal analog/digital neuromorphic electronic circuits provides new means for implementing neural coupled oscillators on compact, low-power, spiking neural network hardware platforms. However, their implementation on this noisy, low-precision and inhomogeneous computing substrate raises new challenges with regards to stability and controllability. In this work, we present a robust, spiking neural network model of neural coupled oscillators and validate it with an implementation on a mixed-signal neuromorphic processor. We demonstrate its robustness showing how to reliably control and modulate the oscillator's frequency and phase shift, despite the variability of the silicon synapse and neuron properties. We show how this ultra-low power neural processing system can be used to build an adaptive cardiac pacemaker modulating the heart rate with respect to the respiration phases and compare it with surface ECG and respiratory signal recordings from dogs at rest. The implementation of our model in neuromorphic electronic hardware shows its robustness on a highly variable substrate and extends the toolbox for applications requiring rhythmic outputs such as pacemakers., Scientific Reports, 11 (1), ISSN:2045-2322

The development of this document is focused on the analysis of two types of soil: greenhouse substrate and earthworm humus mixed with the greenhouse substrate, which have been used to measure important factors, such as temperature, humidity, light, water irrigation, in the germination of Solanum lycopersicum (tomato) seeds, then stored this information in a database, the period of time for evaluation is the fifteen days. To acquire this information, sensors are used, capable of transforming variables such as temperature, environmental humidity, soil humidity, amount of ambient light, into electrical signals that are processed by an electronic microcontroller. This microcontroller is in charge of handling this data, it is also in charge of controlling the use of water irrigation pumps in a closed environment and later storing, in a database, its behavior. In the field of agriculture, the use of electronic hardware is implemented as a tool that helps in this area, presenting sensors to capture data and actuators that are useful for automating conditions such as water irrigation in closed environments.

Today’s world is getting influenced by cutting edge technologies. We have experienced how technology played a key role during COVID-19 pandemic period in all over the world including fields like health sector, information technology, education, finance etc. With the rapid and huge development in electronic hardware technologies in the last decade resulted into Artificial Intelligence (AI) is now driving numerous fields. The homes have been becoming smart since the last decade and now AI is putting intelligence into the smart home forming a smart intelligent home. The things or devices of the smart home are controlled and networked by the means of the Internet of Things (IoT) technology. The computer vision is an emerging field which is embedding a smart vision to IoT based systems including smart home as well. The paper work presented here is based on experimentation with smart home using IoT and Computer Vision technologies.

The agricultural revolution has been a significant factor in driving the modern world’s working economy. Although various robotic and technological advancements are present in this field, no such technology is aimed at poor farmers in developing economies such as the Indian subcontinent. This article proposes a low-cost autonomous vehicle to automate the process sowing the seeds of Maize. The processes that went into the development of the vehicle are comprehensively discussed: First of all, following the standard seed rate and plant geometry for a Maize sample, the seed container and seeder were designed in SolidWorks with efficient design principles. A dual-axis solar tracker was developed for a solar panel that was after extensive energy calculations. A vehicle model was developed to ergonomically accommodate the subsystems mentioned above, as well as the electronic hardware. The frame and other components were statically and dynamically tested for operational stresses using FEA. The electronic hardware, including motors for vehicle propulsion, solar tracking, and the seeder mechanism, all controlled using an Arduino microcontroller, are also discussed comprehensively. This article also discusses the difference in solar panel layouts with experimental data. The vehicle discussed in this article aims to bridge the gap between the field of agriculture and automation by proposing a low-cost solution through efficient designing and manufacturing.

Internet of things (IoT) is the disruptive technology used in the computer automaton. Embedded electronic hardware is connected to Internet in IoT. Connecting IoT devices to the Internet, IoT security becomes the important issue. In this paper, we explain the recent case studies of attacks on IoT devices and network along with vulnerabilities behind each attack. We enlist reasons behind these attacks along with preventive measures to make the IoT devices and network more secure. The paper aims to attract attention of research community toward IoT security.

This paper presents the IOT based smart energy meter to track the energy consumption automatically of the residential load. This meter is capable of sending the consumptions to the consumer as well as an electricity supplier. The readings are taken automatically by using the HLW8012 sensor. Then a predefined set of programs calculates the total bill of energy consumed over the selected interval using the ESP32 microcontroller. The bill is updated in the smartphone by employing a network of Internet of Things. This system eliminates the involvement of the operator for manual methods of taking the meter reading and updating the server for bills. The user can check the number of units consumed by the load at any time using the smartphone. In the future, this idea can be implemented for prepaid metering, which will eventually increase the revenue of the electricity distribution company. We are using ESP32 because of the inbuilt Wi-Fi and Bluetooth facility available in this microcontroller IoT is the combination of collect and exchange data from electronic hardware to the cloud platform and share with the software linked. The platform of the virtual android app is used. Which reflect all the value of Voltage, Current, Power, and unit consumed on the mobile screen.

This work focuses on a specific development aiming towards the detection of human face in an Internet of things (IoT) platform. IoT is a growing wireless based technology, which connects physical objects supported by different forms of electronic hardware. In this work, we propose an IoT application meant for security purpose, where human faces will be analyzed online. The application accepts the face image of a person and tries to find a match with any of the pre-stored facial images in the database. The detection will be automatically validated and the status message can be transferred in real-time to some specified IP address. Initial phase of our work describes the development of a Python program, which works on a Raspberry Pi IoT hardware bearing a small controller fitted with four USB modules. It is connected to the outer world through a Pi Camera, passive infrared (PIR) motion sensor, power supply, secure digital (SD) card, and a 40-pin GPIO port. The next phase of work focuses on estimating the resource requirement and its minimization. The proposed research aims towards a smart technology for robust face detection in an on-field environment.

Automatic gear shifting is a process in which an electronic hardware system is installed in the vehicle and the gear shifts automatically when it moves, without the need for any person to manually shift it. This automation is accomplished through the use of a microcontroller as well as the necessary sensors. The automatic gear shifting system is designed to keep the engine running at optimal revolutions per minute (RPM). The transmission must automatically up-shift as the engine revolutions rise above the top limit. This results in the efficient working of the engine, also increasing its longevity making the task of the driver easier. The microcontrollers communicate with the control systems and other components in the car using the Controller Area Network (CAN) protocol. This work discusses the algorithm involved, the sensors used to achieve the perfect output and safe transmission. Comparing the graphs of the manual transmission and automatic transmission. The proposed work also allows shifting from AMT to manual mode with the use of a simple button controlled using the micro-controller. Finally, the modifications required on the existing car models to achieve higher speeds at a shorter period of time and the improvements in a car after the implementation of the concept.

2020 International Topical Meeting on Microwave Photonics (MWP), The sub-mm wave region of the electromagnetic spectrum, especially the span of 70 GHz centered on the 556.9 GHz H2O water line, offers a rich harvest of highly diagnostic volatile species that provide powerful insights into a planetary body's origins, thermal history, and conditions for habitability. Previous spaceborne Heterodyne Sub-mm Wave Spectrometers (HSWS) process a small fraction of their capable bandwidth at a given moment. The design of each spectrometer channel also depends on a priori knowledge of observable spectral features. Expanding this capability using traditional electronic hardware substantially increases the mass and power consumption of the instrument, limiting its use for CubeSat and SmallSat platforms. Microwave Photonic Integrated Circuits (PIC) is an enabling technology to fabricate an ultra-wideband, high-resolution, sub-mm wave spectrometer that could simultaneously process the receiver's entire bandwidth at a reduced size, weight, and power consumption (SWaP). Through the development of a test platform to combine commercial-off-the-shelf (COTS) and PIC components, we demonstrate the feasibility of a PIC spectrometer.

Sound synthesis refers to the generation of sound using electronic hardware and software. Sound synthesis has many applications, such as creating electronic instruments that resemble real instruments or generate unusual, unique new sounds. Currently, these type synthesized instruments are commonly employed for music production of many different genres of music. The generation of a sound relies on selecting and adjusting many parameters related to the form of base waves, envelope signals, and digital sound filters. Unfortunately, the number of these parameters can be huge. Therefore, creating a new sound can be overwhelming, especially if the user is not familiar with the principles of wave formation. In this work, we present a method based on convolutional neural networks that can be used to generate synthesized sounds from images that depict geometrical figures. Our results indicate the feasibility of employing the proposed methodology for allowing users to create new sounds more easily.

Summary Biological circuits and systems within even a single cell need to be represented by large-scale feedback networks of nonlinear, stochastic, stiff, asynchronous, non-modular coupled differential equations governing complex molecular interactions. Thus, rational drug discovery and synthetic biological design is difficult. We suggest that a four-pronged interdisciplinary approach merging biology and electronics can help: (1) The mapping of biological circuits to electronic circuits via quantitatively exact schematics; (2) The use of existing electronic circuit software for hierarchical modeling, design, and analysis with such schematics; (3) The use of cytomorphic electronic hardware for rapid stochastic simulation of circuit schematics and associated parameter discovery to fit measured biological data; (4) The use of bio-electronic reporting circuits rather than bio-optical circuits for measurement. We suggest how these approaches can be combined to automate design, modeling, analysis, simulation, and quantitative fitting of measured data from a synthetic biological operational amplifier circuit in living microbial cells., Graphical Abstract, Bioelectronics; Engineering; Electrical Engineering

Human Activity recognition has many potential applications in telemedicine and rehabilitation. The advent and recent improvements in deep learning have encouraged the development of more accurate classifiers that were previously unprecedented. The present work focuses on classifying human activity using small, raw datasets collected with instrumented and customized footwear. Multi-channel time series data were recorded and transmitted wirelessly to a recurrent neural network classifier, which was able to classify 6 activities with an accuracy of up to $87. 0 \pm 8. 9$%. Lower level features were detected by the use of convolution. The present work shows that it is possible to use artificial neural network based software techniques to accurately classify data, even with small datasets and low-cost electronic hardware.

To avoid the difficulty of image processing in the gigapixel optical system, this paper proposes a CUDA-based acceleration strategy for the rapid mosaic of a large-scale image and realizes the rapid mosaic of a large-scale image using the collaborative processing of CPU and GPU. Finally, the author designed an electronic hardware and software system and a fast splicing algorithm suitable for the rapid processing of large-scale image-based on a 100-megapixel monocentric multiscale optical system. And the real-time processing of data from nine 12 million pixel sub-cameras at 7.5 frames per second is completed to realize the real-time splicing of the video in the whole field of view.

The safety of electronic hardware devices is always remaining as a major concern in today’s world. With the expanding development of the microelectronics gadgets and application, there is a parallel squeezing more interest in guaranteeing these items’ genuineness, safety, and dependability of its electronic framework. The safety prerequisite for the majority part of these applications is significant and evolving nowadays, similar to this expansion in advance assaults are also build up each day. These assaults regularly have a lot higher effect and basically, no real way to make up for them with extra programming countermeasures on-chip “physical unclonable function (PUF)” are come out as an amazing safety alternative those can be conceivably taken care of security issue. In this paper, a “PUF” framework is proposed which is dependent on LFSR rationale that can be effortlessly executed on “FPGA”. Here another solid “PUF” plan is proposed, which is postponement based “PUF”. Defer based “PUF” utilizes worked in postpone qualities of the physical parts that are inalienable among chip to chip. Easily approval of “integrated circuits(IC)” depends on “PUF” utilization is portrayed. The entire venture is executed utilizing “Verilog HDL” and orchestrated with a “Xilinx Vivado2019.2”. The fundamental point of this task is to concentrate on, fewer areas of the design and relatively low power consumption. It can be smoothly implemented and the right choice for “device authentication” on “FPGA”.

In the context of the Automotive SPICE® standard process reference and assessment models, many works have been published about the standard’s possible and actual interpretations in several industrial environments and applications. Very few of them, however, deal with the question of what detailed electronic hardware development practices can or shall achieve, and in which order they should be performed. Particularly in safety-relevant systems, however, hardware design quality is vital. In this paper, we present an interpretation of Automotive Hardware SPICE as it is practiced within a global tier-2 supplier. We also show its compatibility with the Hardware SPICE process reference and assessment model plug-in released by the intacsTM at the end of 2019.

A low cost, compact embedded design approach for actuating soft robots is presented. The complete design and mode of operation was demonstrated, and the production of the complete system was also demonstrated by building a microcontroller based hardware system which was used to actuate a soft robot for bending motion. The whole system including the electronic circuit board and actuation components was embedded in a 3D-printed casing to ensure a compact approach for actuating soft robots. Results show the viability of the system in actuating and controlling silicon-based soft robots to achieve bending motions. Qualitative measurements of the bending distance and pressure were obtained using this system. This electronic design is easy to reproduce and integrate into any specified soft robotic device requiring pneumatic actuation.