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The Lawrence Berkeley National Laboratory (LBNL) has been developing sensors for the pulp and paper industry that use a magnetic field. The applications for magnetic sensors that have been studied include 1) sensors for the measurement of the water and ice content of wood chips entering the pulping mill, 2) sensors for measuring the water content and other constituents of the black liquor leaving the paper digester, and 3) sensors for measuring paper thickness and water content as the paper is being processed. These tasks can be done using nuclear magnetic resonance (NMR). The magnetic field used for doing the NMR can come from either permanent magnets or superconducting magnets. The choice of the magnet is dependent on a number of factors, which include the size of the sample and field strength needed to do the sensing task at hand. This paper describes some superconducting magnet options that can be used in the pulp and paper industry. [ABSTRACT FROM AUTHOR]

This study outlines the numerous models of automated writing machines that employ diverse technologies, as well as the creative concept of the most recent automatic writing pen. Despite the technologyaccessible, the proportion of compactness and capacity to stand without aid in these machines is almost nil. In contrast to the writing machine, our innovation allows the autonomous writing pen to stand alone without the need for additional support. This pen ensures faultless and exact writing based on the speech recognizing voice sensor or the brain signal detected by a brain sensor. A side from that, the pen has two additional features: it can move the page on its own using a page turner, and it comes preloaded with Pelican for correction. [ABSTRACT FROM AUTHOR]

Soil salinity is an important factor determining agriculture yield and productivity. Sensor technology can be used for monitoring the salinity of soil and this paper consolidates the research trends on the same. The research trends were visualized through VOS viewer and various types of sensors for measuring and monitoring soil salinity had been highlighted. The most active authors of this research domain were Kerr Y.H Camps A and Wigneron J.P; the most active country was the United States of America and the most productive research organization was found to be Centre d'Etudes Spatiales de la Biosphère, France. The recommendations for future research had been highlighted in this paper. [ABSTRACT FROM AUTHOR]

EMG is a medical technique that measures muscle response or electrical activity in response to a nerve’s stimulation of the muscle [10]. In this paper we have classified multiple hand gestures using small number of electrodes. This report aims to review current use of EMG based control system and explain the existing challenges. The stages involved includes data acquisition, feature extraction, classification and controller. Some of the application includes Arm rehabilitation, game controller, wheel chair controllers, etc. [ABSTRACT FROM AUTHOR]

This paper on one hundred and thirty documents on the application of Sensor technology for monitoring of oil pipelines was reviewed and visualization of research trends was prepared using VOS viewer. The consolidation of documents since 2003 was made by using parameters of key authors, regions, keywords, and research institutes. The leading authors, regions, and research organizations were highlighted. The scope for future research can be on various challenges associated with monitoring oil pipelines through sensors. [ABSTRACT FROM AUTHOR]

Learning educational boards are one of the most significant devices in the education of students in universities. This technique, considered for the particular creation of the experimental setting, enables students to learn basic skills quickly and attain successful careers. This paper designs and tests an educational training board to educate students how to set-up the equipment in medical systems. The educational training board consists of many sensors and actuators like electrocardiogram (ECG), heart rate, motion processing unit (MPU), servomotor, DC motor, relay, and ultrasonic sensor (UUS). In addition, to record data and appearance information techniques, there is a mini oscilloscope and LCD. The experimental results were successfully used by 87 students to motivate learners and apply a variety of medical sensor applications. The difference ratio of the educational boards' depending on the opinions of the students is about 8.3%. The educational training board has been aimed at actual experiments. This work has generally involved the progress of an experimental system for several courses to address inadequacies in the teaching of medical sensors. Therefore, this board is an opportunity to teach students to monitor and record signals and learn to avoid mistakes during work and operation. [ABSTRACT FROM AUTHOR]

User-testing is crucial in modern product design. The perception-centric design philosophy aims to cut costs and improve responses to low-cost prototypes by including aspects like thermal properties, texture, weight, sound, and haptic feedback. This paper introduces a set of considerations for integrating low-cost vibrotactile haptics into prototypes. Derived using an action-based research process, it addresses product characterisation, actuation, control, and integration. Multi-sensory prototypes in early-stage design could be vital for the sustainable prototyping of the future. [ABSTRACT FROM AUTHOR]

Many papers have been written about the phenomenon of arc flash, the causes of arc flash, how to fix specific arc flash problems, and how to design arc flash issues out from the beginning. This paper will discuss the overall process of completing an arc flash study and remediation project in a pulp and paper mill. Most plants are not fortunate enough to receive sufficient funding to do the whole study and remediation process all at once. This paper explores how a Midwestern pulp and paper mill worked over several years to get through the process of the study, remediation efforts, and the establishment of an overall Electrical Safety Program. [ABSTRACT FROM PUBLISHER]

This paper present a pedagogical tool to address a lack of creative approach in traditional education on embedded sensors. The tool is built in a systematic way from the data sheet information of a large number of different sensors. The tool presents the main monitoring capabilities of embedded sensors on cards to assist students in the creative stages of product design. An experiment was conducted to test its educational potential with 30 Masters students in product design. The statistical analysis on the experiment data indicate that the tool enables the improvement of knowledge on embedded sensors, with a more significant gain in advanced thinking skills. Finally, the tool is easy to implement in product design education and accessible to a wide range of students. [ABSTRACT FROM AUTHOR]

Swimming activity is a divine gift for humanity by the nature, since it offers health and mental well-being but unfortunately having numerous benefits swimming also leaves so many families in despair due to unintentional deaths. Swimming death that is also called drowning death has several reasons from manmade reasons to atmospheric conditions. The man-made reasons can be prevented by following technological solutions progressively. The current article describes a multilevel safety swimming pool that gives the best safety to swimmers and pets from drowning death. The present design-article introduces a complete novel detailed system of a multi-level swimming pool with the help of sensors and embedded programming. The proposed system in the present paper has given promising results when implemented by a miniature prototype. [ABSTRACT FROM AUTHOR]

In this paper, we present an EMG signal analysis and classification technique for hand gesture recognition specialized for autonomous vehicle environments. In addition, we propose a new user interface method that considers the bio signals received from wearable devices and the characteristics of self-driving cars. EMG is an electrical property produced to command the contraction and relaxation of muscle tissue. The medical surface EMG sensor mounted on the MYO armband used in the experiment transmits EMG signals and sensor information wirelessly from the arm to the terminal via Bluetooth. The EMG-based interaction system proposed in this paper processes the collected EMG signals to classify hand gestures and interacts with the autonomous driving system. Gestures for control transfer are classified in a double threshold method through EMG signal analysis and used as a more efficient interface by applying a separate low pass filter. This EMG-vehicle interaction system was developed to enable control of an autonomous vehicle through a system capable of controlling an autonomous vehicle. In addition, we introduce constraints and methods using vehicle state information to reduce gesture recognition errors that may occur in situations unintended by the driver. [ABSTRACT FROM AUTHOR]

The advancement in electronic systems brings new approaches to make customized electronics at low cost and is easy to make in a simple way. Flexible sensors with paper as substrate are recyclable and biodegradable. Flexible sensors do not require sophisticated procedure like clean room, very high temperature, expensive materials and requirement of vacuum for fabrication. In this paper commercially available FSR406 as force sensor, velosat as pressure sensor & GOP as resistor, capacitor and thermo resistive material are studied and their applications in electronic measurement of physical parameters are done. [ABSTRACT FROM AUTHOR]

Neutron imaging provides additional information to X-ray imaging and can be used in many applications, for example, nuclear engineering, non-industrial diagnostics and homeland security. This paper presents the latest development results of a new 3D structured pixel detector for thermal neutron detection and imaging. The device is based on Medipix/Timepix read-out chip family. The detector, without converter materials, was initially tested in the laboratory with a 241Am source, to simulate events that are induced by reaction products of active material in the silicon bulk. Thanks to the analysis of the size of event clusters and deposited energy, α particles and noise signals were discriminated. The detector was also tested with β and γ sources, to study the effect of other radiation on the device. These results can be useful as a starting point for future experiments, where a neutron source will be used, after filling the cavities with active materials, such as 6Li or 10B. In this paper, the results of the characterization and a comparison between experimental data and Monte Carlo simulations are shown. [ABSTRACT FROM AUTHOR]

High value equipment including aviation turbine engines and medium and large diesel engines require Health and Usage Monitoring Systems (HUMS) which provide actionable and reliable output. Many component failures in oil lubricated systems can be attributed directly to oil condition and contamination, yet the measurement of lubricating oil health using online sensors does not currently provide sufficiently accurate data to facilitate maintenance decisions. In this paper, the direct measurement of oil condition and contamination is discussed through the use of new sensing technologies which give a direct measurement of oil antioxidants and oxidation by-products, as well as quantified measures of water, fuel, coolant, and soot and carbon contamination. By generating unambiguous data and directly measuring individual parameters of the lubricating oil, advanced data processing including physics-based digital twin modelling and machine learning techniques can be applied to the generated data to accurately diagnose lubricant health and identify issues that may affect equipment health. The enhanced model can be used to accurately diagnose lubricant health in near-real-time. This paper presents a novel sensing technology for measuring oil condition accurately in an online, real-time environment, facilitating future work in the development of improved HUMS to facilitate a shift of the most common predictive maintenance tasks to conditionbased maintenance tasks, and ultimately to true predictive maintenance. [ABSTRACT FROM AUTHOR]

Human activity recognition (HAR) using specific information collected from many data acquisition devices such as (camera in video-based activity recognition or sensor in sensor-based activity recognition) which is employed in many types of research domains such as human monitoring, healthcare, and computer-human interaction. This paper provides an overview of the latest papers sensor-based activity recognition and known public datasets used in such papers. Which will gives a diagram of the most recent parts of the accompanying perspectives: significant sign, information catch, and preparing, techniques for managing obscure areas and patterns on the body, choice of fitting highlights, movement models, exercise manuals and measures to evaluate action execution and strategies for surveying the ease of use of the HAR framework. The study covers the identification of repetitive exercises, cases, falls and dormancy. [ABSTRACT FROM AUTHOR]

This research proposes a unique approach to human action recognition using mobile sensor data and a computationally efficient 1D Convolutional Neural Network (1D-CNN). In this research, a 1D-CNN model is constructed to recognize human actions using data from an accelerometer sensor. In order to increase model performance, the study looks into the ideal number of layers and epochs. The proposed method also automates the data annotation to simplify the training process. This research highlights the significance of the chosen model and the size of segments in action recognition. This paper investigates the ideal segmentation size for precisely identifying actions. Experimental analysis confirms the effectiveness of the segmentation length in recognizing human actions by reducing false alarms. This paper demonstrates that increasing the number of fully connected layers does not increase precision or accuracy. The paper concludes by proposing subject-independent methods for action recognition and optimizing power consumption for wearable devices. It highlights the potential of using mobile sensor data and 1D-CNNs for future research in human action recognition. The method and model presented in this paper achieve 95% of recognition accuracy. [ABSTRACT FROM AUTHOR]

The ALICE experiment at the CERN Large Hadron Collider relies on a massive, distributed Computing Grid for its data processing. The ALICE Computing Grid is built by combining a large number of individual computing sites distributed globally. These Grid sites are maintained by different institutions across the world and contribute thousands of worker nodes possessing different capabilities and configurations. Developing software for Grid operations that works on all nodes while harnessing the maximum capabilities offered by any given Grid site is challenging without advance knowledge of what capabilities each site offers. Site Sonar is an architecture-independent Grid infrastructure monitoring framework developed by the ALICE Grid team to monitor the infrastructure capabilities and configurations of worker nodes at sites across the ALICE Grid without the need to contact local site administrators. Site Sonar is a highly flexible and extensible framework that offers infrastructure metric collection without local agent installations at Grid sites. This paper introduces the Site Sonar Grid infrastructure monitoring framework and reports significant findings acquired about the ALICE Computing Grid using Site Sonar. [ABSTRACT FROM AUTHOR]

The Super Tau Charm Facility (STCF) proposed in China is a newgeneration electron–positron collider with center-of-mass energies covering 2-7 GeV and a peak luminosity of 0.5 1035 cm−2 s−1. The offline software of STCF (OSCAR) is developed to support the offline data processing, including detector simulation, reconstruction, calibration as well as physics analysis. To meet STCF's specific requirements, OSCAR is designed and developed based on the SNiPER framework, a lightweight common software for HEP experiments. Besides the commonly used software such as Geant4 and ROOT, several state-ofthe-art software packages and tools in the HEP community are incorporated as well, such as the Detector Description Toolkit (DD4hep), the plain-old-data I/O (podio) and Intel Thread Building Blocks (TBB) etc. This paper will present the overall design as well as some implementation details of OSCAR, including the event data management, paralleled data processing based on SNiPER and TBB as well as the geometry management system based on DD4hep. Currently, OSCAR is fully functioning to facilitate the conceptual design of the STCF detector and the study of its physics potential. [ABSTRACT FROM AUTHOR]

SHiP (Search for Hidden Particles) and the associated SPS Beam Dump Facility is a new general-purpose experiment proposed at the SPS to search for "hidden" particles as predicted by a very large number of recently elaborated models of Hidden Sectors which are capable of accommodating dark matter, neutrino oscillations, and the origin of the full baryon asymmetry in the Universe. SHiP is declared as an experiment with zero background. The Muon Shield is the key element to do this. So on the one hand it has to provide a good background suppression, on the other hand it has not be too heavy. In this paper we present the results of obtaining the new Muon Shield shape using the Bayesian Optimization. This allowed to reduce the background rate by the factor of 2.5, while keeping the weight of the shield at the same level. [ABSTRACT FROM AUTHOR]

The LHCb software stack is developed in C++ and uses the Gaudi framework for event processing and DD4hep for the detector description. Numerical computations are done either directly in the C++ code or by an evaluator used to process the expressions embedded in the XML describing the detector geometry. The current system relies on conventions for the physical units used (identical as what is used in the Geant4 simulation framework) and it is up to the developers to ensure that the correct factors are applied to the values entered. Physical units are not primary entities in the framework, it is therefore not possible to check the dimensional consistency of the computation performed. In this paper we investigate the possibilities to add physical units and dimensions to the existing evaluator or to replace it by a more suitable system, and how this would integrate with the possible tools to express units in C++ code (such as boost::units). [ABSTRACT FROM AUTHOR]

ALICE (A Large Ion Collider Experiment) has undertaken a major upgrade during the LHC Long Shutdown 2. The increase in the detector data rates led to a hundredfold increase in the input raw data, up to 3.5 TB/s. To cope with it, a new common Online and Offline computing system, called O2, has been developed and put in production. The O2/FLP (First Level Processor) system, successor of the ALICE DAQ system, implements the critical functions of detector readout, data quality control and operational services running in the CR1 data centre at the experimental site. Data from the 15 ALICE subdetectors are read out via 8000 optical links by 500 custom PCIe cards hosted in 200 nodes. It addresses novel challenges such as the continuous readout of the TPC detector while keeping compatibility with legacy detector front-end electronics. This paper discusses the final architecture and design of the O2/FLP system and provides an overview of all its components, both hardware and software. It presents the selection process for the FLP nodes, the different commissioning steps and the main accomplishments so far. It will conclude with the challenges that lie ahead and how they will be addressed. [ABSTRACT FROM AUTHOR]

The Front-End Link eXchange (FELIX) readout system is deployed as the new interface connecting detector front-end electronics with the data acquisition and Timing, Trigger and Control (TTC) systems. FELIX functions as a router between custom serial links from front-end ASICs and FPGAs to data collection and processing components via a commodity switched network. FELIX uses commodity server technology in combination with FPGA-based PCIe I/O cards. FELIX servers run a software routing platform serving data to network clients performing a number of data preparation, monitoring and control functions. This paper covers the design of FELIX as well as the first operational experience gained during the Run 3 start, including the challenges faced commissioning the system for each ATLAS sub-detector. Over the next decade, the ATLAS detector will be required to operate in an increasingly harsh collision environment and challenging data taking conditions. To maintain physics performance, the detector will undergo a series of upgrades. In particular, the readout system capabilities will be improved. The planned evolution of FELIX for High-Luminosity LHC will be described, including architectural changes and status of early integration with detector development projects. [ABSTRACT FROM AUTHOR]

The ALICE experiment at CERN has undergone a substantial detector, readout and software upgrade for the LHC Run 3. A signature part of the upgrade is the triggerless detector readout, which necessitates a real time lossy data compression from 1.1 TB/s to 100 GB/s performed on a GPU/CPU cluster of 250 nodes. To perform this compression, a significant part of the software, which traditionally is considered off-line, was moved to the front-end of the experiment data acquisition system, for example the detector tracking. This is the case also for the various configuration and conditions databases of the experiment, which are now replaced with a single homogeneous service, serving both the real-time compression, online data quality checks and the subsequent secondary data passes, Monte-Carlo simulation and data analysis. The new service is called CCDB (for Calibration and Conditions Database). It receives, stores and distributes objects and their metadata, created from online detector calibration tasks and control systems, from offline (Grid) workflows or by users. CCDB propagates the new objects in real time to the Online cluster and asynchronously replicates all content to Grid storage elements for later access by Grid jobs or by collaboration members. The access to the metadata and objects is done via a REST API and a ROOT-based C++ client interface which streamlines the interaction with this service from compiled code while plain curl command line calls are a simple access alternative. In this paper we will present the architecture and implementation details of the components that manage frequent updates of objects with millisecond-resolution intervals of validity and how we have achieved an independent operation of the Online cluster while also making all objects available to Grid computing nodes. [ABSTRACT FROM AUTHOR]

This study explores Machine Learning (ML) integration for household refrigerator efficiency. The ML approach allows to optimize defrost cycles, offering energy savings without complexity or cost escalation. The paper initially presents a State-of-the-Art of ML potential to improve functionality and efficiency of refrigerators. Since frost is the cause of significant energy losses, a ML-based Virtual Sensor was developed to predict frost formation on the evaporator also in low -level refrigerators. The results show the environmental significance of ML in enhancing appliance efficiency. [ABSTRACT FROM AUTHOR]

The understanding of prototyping has changed in recent years to an approach that accompanies the product development process. This paper examines whether classic approaches from product development are also suitable for planning prototyping sequences. The stepwise process-oriented and the problem-oriented approach are discussed. A criticality assessment is proposed as a metric for the prioritization of the functional areas and a procedure is derived from this. The procedure is illustrated using an example. The result is discussed and future steps are suggested. [ABSTRACT FROM AUTHOR]

Nowadays in Synchrotron Light Sources, the state-of-the-art beam position monitors are Diamond XBPM® [1, 2]. They are used in experimental X-ray beam lines for precision measurements and fast control of the beam position and intensity. Diamond is the best-suited low-absorbing detector material due to its low atomic number Z and the use of pure diamond yields a linear signal response. For hard X-rays the application of Diamond XBPM® has no limit. The limits at low photon energies are determined by the thickness of the sensor and the transmission. Diamond detectors can be produced as thin as 3 μm [3], which is adequate with 1.6 keV X-Rays at 50% transmission. Standard thicknesses are 10 μm for 4.3 keV, 20 μm for 5.4 keV and 50 μm for 7.2 keV at 90% transmission. The superior thermal conductivity of diamond allows the highest ionisation levels and highest X-ray beam intensities. Diamond XBPM® are four-quadrant measurement devices. The technological limit for the gap size between the pads is 1 μm. With Diamond XBPM®, however, even beams as small as 60 nm were measured with the highest precision. This is helped by the diffusion of the ionization charge. Diffusion causes a lateral widening of the ionisation channel which increases the measurement precision for small beams. In this paper, we discuss the effect of charge-carrier diffusion in Diamond XBPM®. [ABSTRACT FROM AUTHOR]

The most often utilized strategies for current deep learning models to accomplish a multitude of activities on devices are mobile networks and binary neural networks. In this paper, we suggest a method for identifying and then captioning an object using the pre-trained deep learning (DL) model Mobile-Net for Single Shot Multi-Box Detector (SSD). This technique is utilized for real-time detection as well as webcams to detect the object in a video feed. To construct the module, we use the Mobile-Net and SSD frameworks to provide a faster and effective deep learning-based object detection approach. Deep learning has evolved into a persuasive machine learning mechanization that incorporates various layers of aspects or representations of data to get cutting-edge results. Deep learning has identified excellent performance in a variety of fields, including picture classification, segmentation, and object detection. Deep learning access have newly made important progress in fine-grained picture categorization, which tries to differentiate subordinate-level categories. Major goal of our work is to investigate the accuracy of entity identification method called SSD, further with the significance of pre-trained DL model called Mobile-Net and then captioning the image using Long-Short Term Memory (LSTM) method. The challenge of automatically creating descriptive words for photographs has recently sparked increased interest in computer observation and natural language processing research. It is a machine learning problem that combines computer vision(for understanding image contents) and natural language processing (for text generation). The ability to analyze the state, the properties, and the relationship between these objects is necessary for the meaningful description generating process of high-level picture semantics. [ABSTRACT FROM AUTHOR]

Five cellphones are sold every second, and there are four times more cellphones than computers, meaning there are some billions of mobile handheld devices in existence. Modern cellphones are equipped with multiple context sensors used by increasingly sophisticated software applications that exploit the sensors, allowing the applications to adapt automatically to changes in the surrounding environment, such as by responding to the location and speed of the user. The architecture of such applications is typically layered and incorporates a context-awareness middleware to support processing of context values. While this layered architecture is very natural for the design and implementation of applications, it gives rise to new kinds of faults and faulty behavior modes, which are difficult to detect using existing validation techniques. In this paper we provide scenarios illustrating such faults and exploring how they manifest in context-aware adaptive applications. [ABSTRACT FROM AUTHOR]

The VEML7700 light sensor proves to be an effective instrument for measuring illuminance levels of light sources, and it is frequently employed for this purpose. Demonstrated by students in their conducted experiment, this sensor possesses the capability to accurately measure light across a wide spectrum of intensities, spanning from low to high levels of illumination. The findings indicate that the sensor achieves a very good level of accuracy, with a deviation of only 2 percent. The setup and implementation of the inverse square law of illuminance measurement are explained from various perspectives, including electronics, programming, and user usage. Furthermore, the paper briefly explores other potential measurements that can be conducted utilizing the VEML7700 light sensor. The purpose of the paper with the VEML7700 is to describe a simple and inexpensive measurement for students to verify the method of inverse square law of illuminance, other possibilities are briefly mentioned. [ABSTRACT FROM AUTHOR]

This paper deals with the initial design and realization of a laboratory sample of a birefringent material-based stress sensor. A cube-like sample of commercial polycarbonate (PC) with a volume of approx. 1cm3 is used as an active medium providing information on the applied stress. The sensor uses the stress-induced birefringence of the PC sample for measuring the applied stress. The proposed sensor is calibrated by a commercial weighing element. The utilization of the element allows the conversion of the unknown applied load into a known mechanical stress value according to the known size of the sensing area. In the paper, we report the result of the calibration routine of the sensor sample and discuss the possible application areas. [ABSTRACT FROM AUTHOR]

This paper deals with the max-min and min-max detectors that were introduced in our earlier paper as special cases of generalized detection fusion. Here we investigate theoretical properties of such detectors. For the case of a oneelement background space, we provide the detection region for the max-type detector for an arbitrary shape of the target space. We then show two theorems presenting scenarios when the maxtype detector and the GLR (generalized likelihood ratio) detector are equivalent. In the case when the background and the target spaces are composite, the max-min and min-max detectors may not be equivalent in general and their detection regions may take some complex shapes. Against this backdrop, we specify a fairly general case when the two detectors are equivalent and their detection region boundary is defined by a hyperplane. [ABSTRACT FROM AUTHOR]

The aerospace industry is set to change substantially over the next decade as flight technology evolution makes the skies more accessible and pathways for new technology certification and integration are released by regulators and aircraft manufacturers. If Australia is serious about developing and growing as a technology economy, we must support a sovereign aerospace industry with world class test, trial and evaluation facilities. A national flight test facility for both the air and supporting systems on the ground, is a fundamental industry capability that must be established, supported and developed in Australia purpose built for the next generation of advanced air mobility (AAM). This is a credible opportunity. Most international AAM development is taking place by start-ups which have limited facilities or experience for test and trials activities. Australia with its international reputation for aviation test and evaluation is a credible entrant into AAM T&E. This paper will present the case and planning to establish a sovereign Australian flight test and trial capability for aerospace and advanced air mobility, led by the Aerostructures Innovation Research Hub (AIR Hub), Nova Systems Australia and Latrobe City Council. This capability has been called, Proving Skies, akin to the proving grounds essential to the formation and development of the automotive industry. Proving Skies is being established to allow the safe experimentation, testing, trialling, qualification and verification of AAM and aerospace platforms and technologies and provide the physical to virtual feedback and feedforward loops needed for digital engineering, operations and sustainment. [ABSTRACT FROM AUTHOR]

The Australian Department of Defence's Resilient Multi-Mission Space (RMS) Science, Technology and Research (STaR) Shot is a strategic research program established to develop future space technologies, demonstrating capability through a series of small satellite launches. A key theme of the RMS STaR Shot is to increase the resilience of the satellites and constellations to provide mission assurance for Defence. An important issue for resilience is the effect of atomic oxygen, one of the most significant hazards or risks to satellite materials in the low earth orbit. Materials intended for use on satellites are typically tested in ground-based facilities to match the atomic oxygen fluence experienced during satellite missions. However, in order to correlate these ground-based experiments to in-space results, the atomic oxygen fluence must be accurately measured both on the ground and in-space. The design of atomic oxygen fluence sensors for in-space experiments vary depending on many factors, including mission duration, orbit altitude, and whether or not the experiment is retrievable. This paper provides a review of the current state of art in atomic oxygen fluence sensors for in-space experiments for both retrievable and non-retrievable sensors. The review details the design of several fluence sensors utilised by different space organisations around the world, focusing on those developed recently. The outcome of this research will support resilient technology development in the RMS STaR Shot, as well as calibrating the ground-based extreme environment testing capabilities currently being developed by the Defence Science and Technology Group. The design, manufacture and implementation of an atomic oxygen sensor specifically created for the RMS satellite mission objectives will be essential to validation and verification of in-space atomic oxygen experimental results. [ABSTRACT FROM AUTHOR]

Computerized segmentation of retinal vessels can help doctors discover diabetic retinopathy, Retinal Tear and Retinal Detachment. Because the anatomy of retinal vessels is complicated and changing, automated vessel segmentation is still a difficult task. The Expectation-Maximization approach for retinal vascular segmentation is proposed in this paper, which uses a matched filter (MF) that combines Mask based Blood Vessels Extraction with a global image threshold filter to extract the vessels network. Firstly, the Contrast Limited Adaptive Histogram Equalization method is applied to the retinal image in order to improve the contrast between the blood vessels and the background. Scale Invariant Feature Transform Detector is used to estimate the vessel key point. The expectation maximization technique is used to extract retinal blood vessels, which uses a mask-based blood vessel extraction with a global picture threshold. The evaluation was assessed utilizing ANN to evaluate segmentation performance with Normal and Abnormal Images. The performance of algorithm is compared and analyzed using other approaches. [ABSTRACT FROM AUTHOR]

Reciprocity is an acoustic property that describes the symmetry of sound transmission between two points. However, this property is undesirable in certain applications, and this has led to significant interest in the development of nonreciprocal acoustic devices that achieve one-way sound transmission. These devices typically achieve nonreciprocal sound transmission by introducing nonlinearities or directional biasing. Previously proposed nonreciprocal acoustic devices generally have limitations; for example, they may not be fully tuneable, they can introduce signal distortions such as additional harmonics, or they can only exhibit nonreciprocal behaviour over a narrow bandwidth. To overcome these challenges, previous work has demonstrated how a wave-based active control system can be used to drive an array of acoustic sources to achieve reversible and broadband non-reciprocal behaviour. However these wave-based active control systems use external far-field pressure sensors to achieve broadband nonreciprocal behaviour and, thus, these active control systems are not self-sufficient. This paper therefore presents an experimental investigation into how remote sensing techniques can be incorporated into the previously proposed wave-based active control systems to create more self-contained nonreciprocal acoustic devices that still achieve broadband nonreciprocal behaviour in a one-dimensional acoustic system. [ABSTRACT FROM AUTHOR]

Mutual-Shielding Directional Gamma Detector excels at sensitivity and can achieve good angular accuracy and a large field of view. In this paper, we present, in detail, a method to optimize a mutual shielding directional detector array regarding the scintillators positioning for a given number and size of detection units. The optimization goals are improvement of accuracy and sensitivity. The optimization uses two types of fast, non-Monte-Carlo simulations since the simulation needs to generate measurements from all directions for each array formation tested. Both these simulations are explained and demonstrated. The presented method uses the ambiguity function to assess the accuracy and identify directions that may generate errors due to similar responses from other directions. Then, addressing these problematic directions can be fixed by changing the scintillators' positions or adding a partial shield to change the response at one of the similar directions. [ABSTRACT FROM AUTHOR]

The bulk semi-insulating GaAs material was used for preparation of pad radiation detectors with circular contacts of 1 mm diameter. The spectrometric properties of a semiconductor detector depend on the quality of the base material and on the deposited metallization. Another factor affecting the detector spectrometry is the applied bias controlling the electric collection field. With increasing bias, the charge collection efficiency of particular detector grows. However, this spectrometric property should be changing with detector thickness, which affects the intensity of electric collection field at constant bias applied through the detector sandwich structure. In this paper we have studied the electrical and spectrometric properties of semi-insulating GaAs detectors as a function of their thickness. The measured saturation reverse current was in the range of 3 – 30 nA, increasing with decreasing detector thickness at a substrate resistivity of about of 107 Ωcm. The maximal obtainable charge collection efficiency evaluated from 241Am gamma spectra grew with decreasing detector thickness from 50% for a 450 µm thick detector to 80% for a 230 µm thick detector. [ABSTRACT FROM AUTHOR]

Compton cameras use a pair of detectors to record the energy deposited during Compton scattering and photoabsorption of gamma ray photons. By inverting the forward model for these detection events, the 3D radioactive source distribution can be recovered computationally. However, existing methods of describing the forward model ignore the ambiguity in the Compton cone axis introduced by the detector pixel size. In this paper, we introduce approximations to the axis ambiguity that make the description of the source ambiguity computationally tractable and improve the accuracy of the detection forward model. Specifically, we model the pixel active areas as discs, so the intersection between all possible Compton cone axes and a plane parallel to the detectors is also a disc. Because of ambiguity in the Compton cone axis, the gamma source position is constrained to lie within a more complicated volume that we approximately bound by ellipses or hyperbolas at discrete depth slices. We perform simulations of single point gamma sources using the Geant4 software. Our forward model leads to improved source distribution recovery using both backprojection and iterative reconstruction methods, demonstrating that accurate localization can be performed from a smaller number of detected photons. [ABSTRACT FROM AUTHOR]

Transmission muography is a non-invasive and non-destructive imaging method which allows to estimate the integrated density of a volume in a given direction (also referred as opacity). It relies on a reconstruction of muons tracks that crossed the studied volume compared to the corresponding open sky expectation. The experimental setup of the muography developed at CEA Irfu consists in portable muon telescopes. Each of these instruments has four Micromegas gaseous detectors, power and acquisition electronics, and an embedded computer connected to the network allowing remote control. It is then well adapted to deploy them in constrained environments. A muography measurements campaign has been carried out in the decommissioned nuclear reactors G2 and G3 at CEA Marcoule (France) which are expected to be dismantled. We were able to conduct 2D muographies and 3D analyses of inside G2's airtight concrete chamber. In this paper we describe the measurement protocol at the G2 and G3 reactors. We explain what was developed to improve the measurements between G2 and G3 campaigns. It shows how potential improvements were identified in the proof of concept and why we expect a better reconstruction for G3. Among the improvements, we describe how simulations prior to the measurements, denoising and in general automation play an important role to have a precise 3D image in reasonable time. [ABSTRACT FROM AUTHOR]

Powered by advanced information technology, integrated circuits have been widely involved in various fields. The detection and processing of electrical signals has become one of the important steps. This paper designs a 4-bit absolute value detector using CMOS logic and Pass-Transistor Logic (PTL). It can compare the input binary number with the set threshold, which can detect the peak signal to reduce the interference of noise and improve the detection accuracy of the signal. This paper innovatively uses the full adder to design the absolute value detection part, which can reduce the number of CMOS and reduce energy consumption. To increase driving strength and improve logic delay, the design uses a two-inverter chain as a buffer. To achieve the goal of low energy consumption and low delay, this paper calculates the minimum delay case based on the theory of logic effort and the critical path of the circuit. Through comparing only sizing, only voltage scaling and combining method, the final minimum energy consumption is calculated. The parameters for this design are 12.74 FO4 (0.933V) and 9.58 Eu (0.933V). This means that it can improve the reliability of the device and improve the signal response speed in practical applications. [ABSTRACT FROM AUTHOR]

Traditionally, the design of absolute value detectors has long delay, high energy consumption, and is not accurate enough. The design has been divided into two parts, first taking the absolute value and then comparing with the threshold value. More steps bring more errors and time and energy costs. Therefore, this paper hopes to give a new design that can optimize these problems. In the design, this paper simplifies the traditional two-step design method into one step, and directly compares the size by calculating the difference. In the design, the optimized mirror adder is used, combined with logic calculation and multiplexer (MUX for short), a new design scheme is formed. At the same time, by adjusting the size of the gate and the voltage of the power supply, the power consumption of the circuit is reduced by 68.16% without a significant increase in delay. Coupled with the reduction in the number of devices used in the entire circuit, the overall design in this paper has lower delay and lower energy consumption than traditional methods. [ABSTRACT FROM AUTHOR]

This paper seeks to maximize results by reducing both consumption and propagation delays. The project then tackled the challenge of creating a 4-bit absolute value detector with static CMOS logic and pass transistor logic (PTL) to evaluate the two input values in 2's complement format in a novel way. This paper began by deriving the logical equation from the truth table of an absolute value detector and comparator when creating the project design. This paper then converts the equation into NAND, NOR gates and inverters to simplify the process of computing gate efforts, while also optimizing the topology to reduce the number of transistors and the amount of delay. Subsequently, this article determines the most advantageous gate efforts and total capacitance in order to evaluate the delay and energy expenditure. This paper seeks to balance delay and energy consumption by finding the optimal VDD which is 1.5 times the minimum delay. This paper, in turn, introduced the 4-bit absolute value comparator which decrease the power and delay. The time gap have is 20.586 seconds, which is less than the size-limited condition. This document calculates the ideal VDD value while allowing 1.5 times the minimal delay to achieve a balance between delay and energy efficiency. Consequently, this paper developed the 4-bit absolute value comparator. The delay time is no less than 20.586 seconds when the sizing is taken into consideration. [ABSTRACT FROM AUTHOR]

Absolute value detectors implement a widely used spike-detection algorism called absolute value detection. 4-bit absolute value detectors are extensively used in computer storage and acquiring neural signals. As a basic logic component, there's a rising demand for low energy cost and high working frequency. This paper performed a series of optimizations to the conventional design. A traditional absolute value finder is composed of an absolute value finder using ripple-carry adder and multiplexer, and a comparator. In this paper, both parts are redesigned with static-CMOS logic and transmission gate logic (TGL) to shorten critical path. After the circuit topology is determined, two methods are used to control delay and power consumption: sizing logic gates and adjusting supply voltage. A technique called logic effort is used to derive the delay of critical path. By using a linear programming solver, three sets of parameters are found, in which 38.59-unit delay, 52.75-unit energy cost is a balanced design, with the lowest EDP (Energy delay product). [ABSTRACT FROM AUTHOR]

Wireless sensor network are being utilized in several applications fields such as health care facility, agriculture, military applications, etc. However, the battery incorporated in the system is small in size and has a low power rating which lead to reduced network lifespan. Therefore it is a challenging task for the current wireless networks to utilize the sensor's energy for longer period. In order to overcome these limitations, a number of approaches were proposed in recent years, but the issue that was analyzed in the current approaches were that they were focused on selection of cluster head on basis of convention probability basis approaches. In order to upgrade the resource utilization an energy-efficient control technique that focuses on lowering complexity and increasing network longevity is proposed in this paper. The proposed technique employs a K-Mean clustering approach to form clusters based on network density. In addition to this, a Whale Optimization Algorithm (WOA) is utilized, which considers various QoS parameters such as node residual energy, communication distances and delay and node density. The suggested scheme is tested using the MATLAB software, and performance factors are compared to traditional techniques. Finally, the proposed strategy shows promising results in terms of increasing network lifetime with approx 300 communication rounds, along with less energy consumption, and higher network stability. [ABSTRACT FROM AUTHOR]

High performance ultraviolet (UV) photodetectors are in great demand for strategic applications such as military, flameout protection, missile flame detection and many other applications based on different sub bands of UV detection. Conventional UV detectors are constrained by size, high dark current noise and cost. There is a need for high performance, compact size and less expensive UV detectors. In this paper, a ZnO quantum dot photo-doped graphene/hexagonal Boron Nitride (hBN)/ GaN substrate heterostructure based UV detector is designed, simulated and analyzed for its performance prediction. Electrical and optical characteristics of the device are obtained using a device simulator. The hBN layer at the graphene/GaN interface is used to decrease the dark current. ZnO quantum dot layer deposited on the graphene/hBN/GaN heterojunction help in increasing the responsivity of the device due to its long trapped-charge life time. This detector provides high responsivity in the deep UV to UVA region (100 nm-350 nm) compared to the devices without hBN and ZnO quantum dots layers. [ABSTRACT FROM AUTHOR]

Nowadays, drones are widely employed in a variety of industries. Drones are still not very widespread since they are often expensive and there is a significant danger of harm when flying them. They cannot be flown indoors or in dense forests or areas with many trees. This paper presents a nano drone (drone size below 10 cm) with an obstacle detection feature using LIDAR. The proposed nano drone is used to plot a 2D map of the surrounding and also helps in understanding the path of the flight as well as obstacle sensing. Here the small size and lower cost of components used to make drone makes it more efficient and less risky. The drone consists of an Arduino Pro mini as the processor along with a LIDAR sensor to control the LED and buzzer as indicators. The proposed work results in a small, light nano drone that can fly indoors, over trees, and through gardens while detecting obstacles using LIDAR proximity sensing. [ABSTRACT FROM AUTHOR]

The BESIII experiment is a multi-purpose detector operating at the beams of the electron-positron collider BEPCII in Beijing. Particle tracking is a fundamental part of data analysis for this experiment. The inner part of the BESIII tracker suffers from a strong beam-related background, which significantly reduces tracking efficiency for low-pT tracks and the physics performance of the experiment. The inner part of the tracker will be replaced with the CGEM detector, which is expected to have a better performance in the presence of a strong background. At the same time, it will produce a large number of fake hits. Traditional algorithmic solutions rely on hand-engineered features and metrics, do not parallelize easily, and scale poorly with detector occupancy. In this paper we present our solution for identification and reconstruction of tracks based on deep neural network called TrackNETv2. This model is lightweight, efficient and can be trained using Monte-Carlo simulation. TrackNETv2 was proposed for another experiment BM@N and proved its usefulness for task of particle tracking. Due to architectural restrictions we added some new blocks for this model developing it to TrackNetv2.1. In this paper we evaluated these ideas on simulated data and discussed its strengths and limitations for application in the BESIII tracking challenge. [ABSTRACT FROM AUTHOR]

All over the world new and fast spreading disease have been affecting human health. This led to degradation of the living being's health immunity, support system, mental and physical stability. So the need of assistance requirement for all bed ridden patients is an increasing demand on daily basis. In our present situation the COVID-19 virus's crisis have caused a drastic change to the world. An enormous number of fields such as destruction of employment, economic losses, pandemic growth, food supplies and etc. have been affected. In this paper, an initiative step towards the replacement of man power supply to take care of COVID-19 patients have been proposed. A flex sensor glove wore by a patient would be able to communicate commands to the nurse or a care taker. The system consists of a 2.2 and 4.5 inches' flex sensors fixed over the right hand of the patient, connected with a microcontroller and wireless transmission unit. A corresponding receiver unit would be placed in the nurse station or to the care taker. The movement of patient's hand is associated to different commands. This reduces the need of the nurse to accompany a patient for 24 hours, in this crisis situation and also supports them with an electronic assistance. This flex controlled assist device have been designed and tested with an accuracy of 82.85%. [ABSTRACT FROM AUTHOR]

For future healthcare systems to take advantage of sensor-based patient monitoring devices, careful consideration must be taken in respect to the impact they can have on existing workflow processes. In association with this, data and information quality dimensions need to be incorporated to help ensure a successful outcome. This paper will explore the utilisation of a paper-based patient assessment scorecard and the transition to an electronic version with a view to the future adoption of sensor-based devices. To evaluate the transition from paper-based to sensor-based solutions, the Modified Early Warning Scorecard (MEWS) is the primary exemplar within this paper. MEWS has a defined set of protocols and guidelines that assist the healthcare providers in classifying a patient's status of health in detecting patient deterioration. Paper-based MEWS are already deployed within Medical Assessment Units (MAU). Thus, the MAU is an ideal test bed for the evaluation of sensor-based solutions. The Socio-Technical Information Systems Design (STISD) science research framework is the methodology employed to address a practical problem (i.e. frequent capturing of patient vital signs) raised by the healthcare providers in relation to MEWS. In accordance with the STISD framework, a review of the extant theories, knowledge and data reveal an Event-driven Process Chain (EPC) diagram for the paper-based MEWS. Based on these findings an electronic version of the paper-based MEWS (eMEWS) is proposed and tested. Further refinements are required to explore the full capabilities of sensor-based solutions and the role they can play within MEWS. Presented is a conceptual model which examines the relationship between the content and system quality measures and their associated independent variables. Alpha and gamma tests are conducted to evaluate the eMEWS against the desired outcomes and provide the foundation for the development of the sensor-based eMEWS solution. Results show that the eMEWS prototype addresses key data quality dimensions, with sensor-based eMEWS indicting potential enhancement to the timeliness and frequency of data capturing. [ABSTRACT FROM AUTHOR]

Regenerative Anti-lock Braking System (ABS) is a braking system in vehicle electric (electric vehicle) which can prevent locking on vehicle wheel and do recovery kinetic energy braking into a battery charge. In this paper, regenerative ABS applied in quarter car model approach. Regenerative ABS had many components in it one of them is a sensor. The sensor fault can reduce the safety level of the regenerative ABS. In this paper, Active Fault Tolerant Control (AFTC) scheme is applied to ABS regenerative ABS to accommodate the wheel speed sensor fault to improve system performance. Sliding Mode Controller is used in this regenerative ABS controller with k and epsilon (ɛ) gain parameters 10 and 3 with a maximum overshoot of 18.95%, error steady state 0% and settling time of 0.08 seconds. Then, the AFTC algorithm works by using the residual calculation result ... as the compensation value of the measurement signal. From the results of the response test after being applied the bias and sensitivity fault, the system that equipped with AFTC algorithm able to overcome the sensor fault up to 100%. [ABSTRACT FROM AUTHOR]