Hardware Components Research Articles

Magazine Identification on SS1-V1 Assault Rifle using Web-based HX711 Load Cell Sensor

The SS1-V1 is an assault rifle model equipped with a magazine as one of its main components. The magazine plays a crucial role in storing and loading ammunition. However, magazines must be stored separately from the weapon as their integrated storage can pose a risk to a country’s security. Therefore, this research proposes a web-based system capable of identifying the presence of magazines in weapons in real-time. This system is supported by various hardware components, including a load cell sensor, HX711 sensor module, Arduino UNO R3, and an Ethernet shield for network connectivity. In addition, API is used for data management, which is then stored in the database. The results of this research indicate that the average response time for each rack within a cabinet is between 2.7s to 3.3s, while for racks serving as slaves, it ranges from 14.16s to 15.01s. Based on the results of the weight-based weapon identification testing, there is a weight difference of 0.1kg to 0.2kg. These results state that all tests were successfully identified by the web system according to the conditions of the weapons on the rack.

FMB: A functional manipulation benchmark for generalizable robotic learning

In this paper, we propose a real-world benchmark for studying robotic learning in the context of functional manipulation: a robot needs to accomplish complex long-horizon behaviors by composing individual manipulation skills in functionally relevant ways. The core design principles of our Functional Manipulation Benchmark (FMB) emphasize a harmonious balance between complexity and accessibility. Tasks are deliberately scoped to be narrow, ensuring that models and datasets of manageable scale can be utilized effectively to track progress. Simultaneously, they are diverse enough to pose a significant generalization challenge. Furthermore, the benchmark is designed to be easily replicable, encompassing all essential hardware and software components. To achieve this goal, FMB consists of a variety of 3D-printed objects designed for easy and accurate replication by other researchers. The objects are procedurally generated, providing a principled framework to study generalization in a controlled fashion. We focus on fundamental manipulation skills, including grasping, repositioning, and a range of assembly behaviors. The FMB can be used to evaluate methods for acquiring individual skills, as well as methods for effectively combining and ordering such skills in order to solve complex, multi-stage manipulation tasks. We also offer an imitation learning framework that includes a suite of policies trained to solve the proposed tasks. This enables researchers to utilize our tasks as a versatile toolkit for examining various parts of the pipeline. For example, researchers could propose a better design for a grasping controller and evaluate it in combination with our baseline reorientation and assembly policies as part of a pipeline for solving multi-stage tasks. Our dataset, object CAD files, code, and evaluation videos can be found on our project website: https://functional-manipulation-benchmark.github.io .

Implementation of smart wheelchair with obstacle avoidance

The primary goal of this work is to develop a dependable and efficient solution for maintaining optimal mobility in wheelchair systems. The aim is to enhance functionality and reduce the user’s physical effort required to move the wheelchair wheels. The proposed system integrates advanced sensing technology, intelligent control algorithms, and robust hardware components to manage the wheelchair, detect obstacles, and eliminate the need for external assistance. This wheelchair employs joystick control and halts when the system senses an obstacle. The system enhances user autonomy by providing ease of control and ensures safety by detecting and avoiding obstacles. Motor speeds are adjusted based on joystick input, and the motor direction (forward, backward, left, right) is determined accordingly. An ultrasonic sensor measures obstacle distance, and if an obstacle is detected (distance <= 20cm), both motors stop, and a warning buzzer activates for 1 second. If no obstacle is detected, the warning buzzer turns off, and motor speeds are adjusted based on joystick input. The system effectively demonstrated obstacle avoidance by changing direction when a command was issued away from the obstacle. The outcomes of this study contribute valuable insights to the field of wheelchairs, specifically in the realm of obstacle avoidance.

An MTCA-based LLRF prototype system of LINAC in Hefei Advanced light facility

The linear accelerator (LINAC) system currently under construction at the Hefei Advanced Light Facility (HALF) employs acceleration tubes to accelerate the electron beam to 2.2 GeV. The RF field within the acceleration tube is controlled by an MTCA.4-based low-level radio frequency (LLRF) prototype system to meet stringent phase stability requirements. This paper introduces the structure of the LLRF system, encompassing both its hardware and software components. The LLRF system uses the non-IQ-sampling method to suppress odd harmonics through digital filters, achieving a signal-to-noise ratio (SNR) of approximately 73 dB. Given that the power sources of most acceleration tubes operate in a saturated state, the radio-frequency (RF) control algorithm within the software is based on a separate amplitude open-loop and phase close-loop to maintain stable phase control during amplitude disturbances. The design of the RF control logic, including digital filters, the REF phase tracking method, the close-loop feedback controller, and the output pulse mode control algorithm, is detailed. Offline pulse-to-pulse test results demonstrate that it achieves a phase stability of 0.0176° rms with a solid-state amplifier, meeting the facility's requirements.

AUTOSAR-Compatible Level-4 Virtual ECU for the Verification of the Target Binary for Cloud-Native Development

The rapid evolution of automotive software necessitates efficient and accurate development and verification processes. This study proposes a virtual electronic control unit (vECU) that allows for precise software testing without the need for hardware, thereby reducing developmental costs and enabling cloud-native development. The software was configured and built on a Hyundai Autoever AUTomotive Open System Architecture (AUTOSAR) classic platform, Mobilgene, and Renode was used for high-fidelity emulations. Custom peripherals in C# were implemented for the FlexTimer, system clock generator, and analog-to-digital converter to ensure the proper functionality of the vECU. Renode’s GNU debugger server function facilitates detailed software debugging in a cloud environment, further accelerating the developmental cycle. Additionally, automated testing was implemented using a vECU tester to enable the verification of the vECU. Performance evaluations demonstrated that the vECU’s execution order and timing of tasks and runnable entities closely matched those of the actual ECU. The vECU tester also enabled fast and accurate verification. These findings confirm the potential of the AUTOSAR-compatible Level-4 vECU to replace hardware in development processes. Future efforts will focus on extending capabilities to emulate a broader range of hardware components and complex system integration scenarios, supporting more diverse research and development efforts.

Concept of flexible no-code automation for complex sample preparation procedures

Driven by demographic changes and dwindling Science Technology Engineering Mathematics enrolments, our research introduces no-code automation as a strategic response, aimed at mitigating labor shortages while enhancing productivity and safety in the laboratory environment. Employing a user-friendly, no-code software platform, we automated a complex HPTLC assay, enabling laboratory personnel to configure and modify workflows without requiring specialized programming skills. The manuscript outlines the deployment of a collaborative robot (cobot), a programmable logic controller (PLC), and the utilization of self-developed open-source hardware components to establish automated stations for sample handling, incubation, spraying, detection, and storage within the assay process. The research addresses challenges such as the handling of fragile HPTLC plates and the seamless integration of automated stations, solved through innovative design solutions and adaptive programming methods. This investigation demonstrates the feasibility and efficiency of no-code automation in overcoming skilled labor deficits.

Assessing the Benefits and Challenges of Virtual Reality in Education

Virtual Reality (VR) is a technical advancement that places people in a computer-generated environment and enables them to interact with a three-dimensional world in a way that appears real or tangible by employing specialized electronic gear, including gloves with sensors or a screen-equipped headset. Creating a digital environment where the lines between the real and virtual worlds are blurred in order to provide an experience that may either equal or surpass the complexity of the actual world is the core idea behind virtual reality. Hardware, software, and the user's sensory experience are the three main parts that make up VR foundations. VR headsets, motion controllers, and occasionally other sensory apparatuses that monitor user motions and mirror them in the virtual environment are the standard hardware components. The virtual surroundings, however, are created and rendered by the program. Complicated algorithms are used by this program to create interactive parts that react to human input, replicate physical laws, and create 3D visuals. In order to provide the user a sensation of presence or immersion in the virtual world, VR seeks to completely engage the user's senses, namely sight and sound. So, sensory perception is essential.

Restoration of grasping in an upper limb amputee using the myokinetic prosthesis with implanted magnets.

The loss of a hand disrupts the sophisticated neural pathways between the brain and the hand, severely affecting the level of independence of the patient and the ability to carry out daily work and social activities. Recent years have witnessed a rapid evolution of surgical techniques and technologies aimed at restoring dexterous motor functions akin to those of the human hand through bionic solutions, mainly relying on probing of electrical signals from the residual nerves and muscles. Here, we report the clinical implementation of an interface aimed at achieving this goal by exploiting muscle deformation, sensed through passive magnetic implants: the myokinetic interface. One participant with a transradial amputation received an implantation of six permanent magnets in three muscles of the residual limb. A truly self-contained myokinetic prosthetic arm embedding all hardware components and the battery within the prosthetic socket was developed. By retrieving muscle deformation caused by voluntary contraction through magnet localization, we were able to control in real time a dexterous robotic hand following both a direct control strategy and a pattern recognition approach. In just 6 weeks, the participant successfully completed a series of functional tests, achieving scores similar to those achieved when using myoelectric controllers, a standard-of-care solution, with comparable physical and mental workloads. This experience raised conceptual and technical limits of the interface, which nevertheless pave the way for further investigations in a partially unexplored field. This study also demonstrates a viable possibility for intuitively interfacing humans with robotic technologies.

PHIGrader: Evaluating the effectiveness of Manifest file components in Android malware detection using Multi Criteria Decision Making techniques

The popularity of the Android operating system has itself become a reason for privacy concerns. To deal with such malware threats, researchers have proposed various detection approaches using static and dynamic features. Static analysis approaches are the most convenient for practical detection. However, several patterns of feature usage were found to be similar in the normal and malware datasets. Such high similarity in both datasets’ feature patterns motivates us to rank and select only the distinguishing set of features. Hence, in this study, we present a novel Android malware detection system, termed as PHIGrader for ranking and evaluating the efficiency of the three most commonly used static features, namely permissions, intents, and hardware components, when used for Android malware detection. To meet our goals, we individually rank the three feature types using frequency-based Multi-Criteria Decision Making (MCDM) techniques, namely TOPSIS and EDAS. Then, the system applies a novel detection algorithm to the rankings involving machine learning and deep learning classifiers to present the best set of features and feature type with higher detection accuracy as an output. The experimental results highlight that our proposed approach can effectively detect Android malware with 99.10% detection accuracy, achieved with the top 46 intents when ranked using TOPSIS, which is better than permissions, hardware components, or even the case where other popular MCDM techniques are used. Furthermore, our experiments demonstrate that the proposed system with frequency-based MCDM rankings is better than other statistical tests such as mutual information, Pearson correlation coefficient, and t-test. In addition, our proposed model outperforms various popularly used feature ranking methods such as Chi-square, Principal Component Analysis (PCA), Entropy-based Category Coverage Difference (ECCD), and other state-of-the-art Android malware detection techniques in terms of detection accuracy.

Optimizing Real-Time Advanced Ultrasound Supervision in a University Setting

Introduction: Ultrasound-based diagnosis requires great expertise for reliability and accuracy, thus practical training is vital. Digital training can offer students the possibility of practical training in their local setups. However, there are critical issues that remote educators must address, particularly in advanced ultrasound training. The present study was therefore aiming at developing a suitable technical setup for supervision and education in tele-ultrasound that can be applied to a variety of advanced diagnostic and therapeutic areas. Methods: Using an action research approach including four cycles of action, we tested four technical setups with different software and hardware components across four ultrasound courses. Based on evaluation forms, written reflections, and two focus group interviews from the four cycles of action, respectively, we modified the setups to improve the technical solution for the next cycle. Results: The initial set-up was using commercial video call apps via mobile phones. Although no additional equipment or expertise was required, it was precluded by the poor image quality and motion blur resulting from capturing the ultrasound image on the smartphone. Nevertheless, this solution is viable when quick clarifications are needed. Additional stabilization support in the second set-up did not provide satisfactory image quality. The best technical solution was found in the third set-up, using a frame grabber and Reacts, which allows simultaneous live streaming of the ultrasound screen image and two web cameras. However, the cumbersome software interface, the need for an expensive user license, and problems with the internet connection reduced the acceptability of this setup. The optimal setup in cycle four, was a reasonable frame grabber, and Zoom, which is free, has a simple user interface and can stream live audio-visual ultrasound data from the probe and user simultaneously. Its annotation function is also beneficial in supervision. Conclusion: Through an action research approach including four cycles of action and thorough, subsequent evaluations, we found that a videoconferencing platform, such as Zoom, a computer, and a frame grabber connected to the ultrasound scanner was the optimal solution as this set-up is simple and affordable and is facilitating a good video-transmitted learning situation for students and supervisors. This technical set-up could therefore be suitable for a wide range of remote ultrasound courses.

Second-order mean-field approximation for calculating dynamics in Au-nanoparticle networks.

Exploiting physical processes for fast and energy-efficient computation bears great potential in the advancement of modern hardware components. This paper explores nonlinear charge tunneling in nanoparticle networks, controlled by external voltages. The dynamics are described by a master equation, which expresses the time-evolution of a distribution function over the set of charge occupation numbers. The driving force behind this evolution is charge tunneling events among nanoparticles and their associated rates. We introduce two mean-field approximations to this master equation. By parametrization of the distribution function using its first- and second-order statistical moments, and a subsequent projection of the dynamics onto the resulting moment manifold, one can deterministically calculate expected charges and currents. Unlike a kinetic Monte Carlo approach, which extracts samples from the distribution function, this mean-field approach avoids any random elements. A comparison of results between the mean-field approximation and an already available kinetic Monte Carlo simulation demonstrates great accuracy. Our analysis also reveals that transitioning from a first-order to a second-order approximation significantly enhances the accuracy. Furthermore, we demonstrate the applicability of our approach to time-dependent simulations, using Eulerian time-integration schemes.

Data losses and synchronization according to delay in PLC-based industrial automation systems

PLC (Programmable Logic Controllers) based data collection is integral to industrial automation and data acquisition processes. The pipeline – between the device and the database – is a complex system with many components and often causes some time delay, due to the synchronization and the applied hardware and software components. This delay can also lead to data loss on the database site. In this study, we aimed to examine this problem connected to the synchronized behavior of four counter networks within the TIA software for PLCs, particularly focusing on the implications of a 1 Hz (Hz) clock frequency on counter synchronization. Meticulous experiments were conducted and the integration of Node-RED, as an instrumental tool in industrial automation, facilitated counter-behavior monitoring. Recorded values of counter and timestamps were meticulously stored in four separate databases (MSSQL, MySQL, MongoDB, and Apache Cassandra) for comprehensive data analysis. Throughout the experiments, inconsistencies in the counter values were encountered, leading to the discovery of missing values that varied across the ten tests. To detect the reason, a unique delay calculation method was developed. According to our results, we were able to do post-synchronization with millisecond-level accuracy. It can help reveal the missing values that depend on the Node-RED and the PLC cycle time differences.

Securing high-value electronic equipment: an internet of things driven approach for camera security

<p>This article addresses pressing challenge of securing high-value electronic equipment, notably cameras, which face dual threats of damage in high humidity conditions and theft due to their significant market value. To confront these issues, the study introduces innovative internet of things (IoT)-driven approach aimed at strengthening conventional storage box security. Central to this approach is integration of IoT technologies, such as Arduino and ESP32, to develop advanced safety storage box. This enhanced system features essential hardware components, including buzzer, password-protected keypad, radio frequency identification reader, and DHT11 sensor for humidity monitoring. Additionally, mobile alarm system is incorporated to promptly alert owners of any detected movement vibrations, thereby augmenting security measures. By leveraging these components, proposed methodology seeks to mitigate risks associated with camera theft and fungal contamination, thereby advancing electronic device security. The expected outcome is marked enhancement in protection of high-value electronic equipment, particularly cameras, through continuous real-time monitoring and proactive security measures. This research underscore’s critical role of IoT technologies in fortifying security measures for valuable electronic assets, contributing significantly to ongoing discourse on innovative strategies in field. Through its comprehensive approach, this study aims to offer practical solutions to mitigate security risks and safeguard electronic equipment against potential threats, thereby addressing critical need in realm of electronic device security.</p>

Personalized low-cost thermal comfort monitoring using IoT technologies

Thermal comfort plays an essential role in the well-being and productivity of occupants. Typically, thermal comfort is assessed either through surveys completed by building occupants or through sensor data that is analyzed using thermal comfort models. Automating comfort surveys and data collection processes reduce the risk of information loss, providing more accurate and personalized thermal comfort assessments over longer periods of time. To this end, this paper presents the design and implementation of a thermal comfort monitoring system consisting of low-cost hardware components and using IoT technologies. The system consists of intelligent wireless sensor nodes that collect and process environmental data, a portable main station that integrates and stores data, and a digital survey that provides feedback from building occupants. To ensure accuracy, the low-cost hardware components of the intelligent sensor nodes are calibrated in a climate chamber, using high-precision sensors for reference. After calibration, the system is deployed in a field test where several intelligent sensor nodes collect environmental data in an office, while occupants complete the digital thermal comfort survey. In addition, thermal comfort indexes are computed by the intelligent sensor nodes and compared with the feedback of each building occupant. The results indicate that the low-cost thermal comfort monitoring system successfully collects and integrates thermal comfort data from the intelligent sensor nodes and the digital survey, being able to create personalized thermal comfort profiles. In future work, the system can be used in large-scale thermal comfort surveys, to develop personalized thermal comfort models and to control personalized comfort systems.

A comprehensive engineering design analysis of Apple Watch as a smart wearable device

This paper presents a comprehensive engineering design analysis of the Apple Watch, a pioneering smart wearable device by Apple Inc. The analysis covers the device's hardware and software components, design principles, manufacturing processes, impact on user experience, and its influence on the wearable technology market. The Apple Watch integrates advanced technologies into a sleek and functional design, enhancing user interaction through its intuitive interface and robust health monitoring capabilities. By examining its engineering intricacies and market impact, this study highlights the Apple Watch's role in shaping the future of wearable technology.

Synthesis of Self-Checking Circuits for Train Route Traffic Control at Intermediate Stations with Control of Calculations Based on Weight-Based Sum Codes

When synthesizing systems for railway interlocking, it is recommended to use automated models to implement the logic of railway automation and remote control units. Finite-state machines (FSMs) can be implemented on any hardware component. When using relay technology, the functional safety of electrical interlocking is achieved by using uncontrolled (safety) relays with a high coefficient of asymmetry of failures in types 1 → 0 and 0 → 1. When using programmable components, the use of backup and diverse protection methods is required. This paper presents a flexible approach to synthesizing FSMs for railway automation and remote control units that offer both individual and route-based control. Unlike existing solutions, this proposal considers the pre-failure states of railway automation and remote control units during the finite-state machine synthesis stage. This enables the implementation of self-checking and self-diagnostic modules to manage automation units. By increasing the number of states for individual devices and considering the states of interconnected objects, the transition graphs can be expanded. This expansion allows for the synthesis of the transition graph of the control subsystem and other systems. The authors used a field-programmable gate array (FPGA) to implement a finite-state machine. In this case, the proposal is to encode the states of a finite-state machine using weight-based sum codes in the residue class ring based on a given modulus. The best coverage of errors occurring at the outputs of the logic converter in the structure of the FSM can be ensured by selecting the weighting coefficients and the value of the module. This paper presents an example of synthesizing an FPGA-based FSM using state encoding through modular weight-based sum codes. The operation of the synthesized device was modeled. It was found to operate according to the same algorithm as the real devices. When synthesizing self-checking and self-controlled train control devices, it is recommended to consider the solutions proposed in this paper.

IoT IP Overlay Network Security PerformanceAnalysis with Open Source Infrastructure Deployment

Some of the most deployed infrastructures nowadays are Overlay Networks (ONs). They consist of hardware and software components designed to establish private and secure communication channels, typically over the Internet. ONs are among the most reliable technologies for achieving this objective and represent the next-generation solution for secure communication. In this paper, we analyze important network performance metrics (RTT, bandwidth) while varying the type of Overlay Network used for interconnecting traffic between two or more hosts (within the same data center, in different data centers in the same building, or over the Internet). These networks establish connections between KVM (Kernel-based Virtual Machine) instances rather than the typical Docker/LXC/Podman containers. The first analysis will assess network performance as it is, without any overlay channels. The second will establish various types of channels without encryption, and the final one will encapsulate overlay traffic via IPsec (Transport mode), where encrypted channels like VTI are not already available for use. The obtained performance is demonstrated through a comprehensive set of traffic-simulation campaigns.

Delayed Wound Healing in a Young Patient with TNXB Variants and the Role of WES

After decades of quality improvement efforts, surgical site infections and abnormal wound healing remain intermittent complications in surgery. In both cases, the complication and abnormality may be superficial, restricted to the skin, or deeper within the tissue. The synthesis of connective tissue proteins, critical for structural support as part of the extracellular matrix, is under the control of multiple genes, forming a complex adaptive network. We report an unusual case of delayed and abnormal wound healing with chronic infection in a 16-year-old patient following surgery for scoliosis. Skin patch test showed that he is allergic to cobalt, a component of fixation hardware used in his surgery. He underwent evaluation by clinical genetics with whole exome sequencing (WES) which showed two (maternally and paternally inherited) variants in the TNXB ( Tenasin XB) gene. These two variants are variants of uncertain significance (VUS). TNXB encodes tenascin-XB which is an extracellular matrix glycoprotein located primarily in the basement membrane. Autosomal recessive pathogenic and likely pathogenic variants in TNXB cause TNXB-related classical-like Ehlers-Danlos Syndrome. At present, there are no causal linkages of these VUSs in TNXB to abnormal wound healing. However, as WES becomes more affordable, its use will increase and therefore it is important that we start to document such associations.

Clinical Advances in Cardiovascular Computed Tomography: From Present Applications to Promising Developments.

This review aims to provide a profound overview on most recent studies on the clinical significance of Cardiovascular Computed Tomography (CCT) in diagnostic and therapeutic pathways. Herby, this review helps to pave the way for a more extended but yet purposefully use in modern day cardiovascular medicine. In recent years, new clinical applications of CCT have emerged. Major applications include the assessment of coronary artery disease and structural heart disease, with corresponding recommendations by major guidelines of international societies. While CCT already allows for a rapid and non-invasive diagnosis, technical improvements enable further in-depth assessments using novel imaging parameters with high temporal and spatial resolution. Those developments facilitate diagnostic and therapeutic decision-making as well as improved prognostication. This review determined that recent advancements in both hardware and software components of CCT allow for highly advanced examinations with little radiation exposure. This particularly strengthens its role in preventive care and coronary artery disease. The addition of functional analyses within and beyond coronary artery disease offers solutions in wide-ranging patient populations. Many techniques still require improvement and validation, however, CCT possesses potential to become a "one-stop-shop" examination.

Leveraging the innovation index (IVI): A research, development, and innovation-centric measurement approach

BackgroundIn today’s rapidly changing business landscape, innovation is recognized as a critical driver of growth and competitiveness for organizations. As businesses strive to remain agile and respond to evolving customer demands, the need for effective tools to assess innovation performance has become increasingly vital.Problem Statement: To better understand Research, Development, and Innovation (RD&I) projects, it might be valuable to investigate and implement new approaches to improve the current innovation indexes. Such exploration could allow for a more detailed and nuanced analysis, enabling a comprehensive evaluation of various aspects of the projects. It may be beneficial to explore ways to enhance the current innovation indexes to provide more nuanced and comprehensive insights into RD&I projects. Traditional indexes are not designed to account for the uncertainty, non-linear progression, and the necessity for long-term impact assessment of RD&I projects. Moreover, projects that involve both hardware and software components introduce additional complexities due to their interdisciplinary nature, integration challenges, and differing lifecycle speeds, making their assessment particularly challenging. GoalThis paper describes the conceptualization and evaluation of the InnoVation Index (IVI), underscoring its role in the innovation assessment within the complex landscape of RD&I projects, focusing on those involving hardware and software components. MethodThe methodology comprised a two-fold process. Initially, a literature review was conducted to comprehensively understand existing innovation indexes and their shortcomings, especially in hardware and software projects. Drawing on the insights from this review and leveraging the expertise of innovation specialists, we formulated the conceptual framework of the IVI. Subsequently, the IVI was implemented in an RD&I Centre affiliated with a public university in Brazil. ResultsThe IVI evaluation encompassed over 40 projects from collaborations with about 20 global IT companies. Rigorous data collection procedures were employed, involving at least three data collection sessions for different phases of each project. More than 150 data collection sessions engage project managers and business professionals to provide a comprehensive and in-depth understanding of the project activities and their innovation levels. Using the IVI measurement, we successfully identified “disruptive”, “potentially disruptive”, “potentially innovative”, and “non-innovative” projects, allowing stakeholders to tailor their strategies and resource allocation accordingly. ConclusionThe application of the IVI has proven instrumental in aiding stakeholders in decision-making, resource allocation, and project activity realignment. These results underscore the pivotal role of the IVI in overcoming the limitations inherent in traditional indexes, offering a tailored and efficient approach to assess and enhance innovation efforts within the RD&I context, especially in projects that bridge hardware and software domains.