bluuebunny/crossref_metadata_2025 huggingface dataset:
Internet-of-Things-Enabled Markerless Running Gait Assessment from a Single Smartphone Camera
Authors: Young Fraser , Mason Rachel , Morris Rosie , Stuart Samuel , Godfrey Alan
Published: January 2023

Running gait assessment is essential for the development of technical optimization strategies as well as to inform injury prevention and rehabilitation. Currently, running gait assessment relies on (i) visual assessment, exhibiting subjectivity and limited reliability, or (ii) use of instrumented approaches, which often carry high costs and can be intrusive due to the attachment of equipment to the body. Here, the use of an IoT-enabled markerless computer vision smartphone application based upon Google’s pose estimation model BlazePose was evaluated for running gait assessment for use in low-resource settings. That human pose estimation architecture was used to extract contact time, swing time, step time, knee flexion angle, and foot strike location from a large cohort of runners. The gold-standard Vicon 3D motion capture system was used as a reference. The proposed approach performs robustly, demonstrating good (ICC(2,1) > 0.75) to excellent (ICC(2,1) > 0.90) agreement in all running gait outcomes. Additionally, temporal outcomes exhibit low mean error (0.01–0.014 s) in left foot outcomes. However, there are some discrepancies in right foot outcomes, due to occlusion. This study demonstrates that the proposed low-cost and markerless system provides accurate running gait assessment outcomes. The approach may help routine running gait assessment in low-resource environments.
Raw Beef Patty Analysis Using Near-Infrared Hyperspectral Imaging: Identification of Four Patty Categories
Authors: Edwards Kiah , Hoffman Louwrens C. , Manley Marena , Williams Paul J.
Published: January 2023

South African legislation regulates the classification/labelling and compositional specifications of raw beef patties, to combat processed meat fraud and to protect the consumer. A near-infrared hyperspectral imaging (NIR-HSI) system was investigated as an alternative authentication technique to the current destructive, time-consuming, labour-intensive and expensive methods. Eight hundred beef patties (ca. 100 g) were made and analysed to assess the potential of NIR-HSI to distinguish between the four patty categories (200 patties per category): premium ‘ground patty’; regular ‘burger patty’; ‘value-burger/patty’ and the ‘econo-burger’/’budget’. Hyperspectral images were acquired with a HySpex SWIR-384 (short-wave infrared) imaging system using the Breeze® acquisition software, in the wavelength range of 952–2517 nm, after which the data was analysed using image analysis, multivariate techniques and machine learning algorithms. It was possible to distinguish between the four patty categories with accuracies ≥97%, indicating that NIR-HSI offers an accurate and reliable solution for the rapid identification and authentication of processed beef patties. Furthermore, this study has the potential of providing an alternative to the current authentication methods, thus contributing to the authenticity and fair-trade of processed meat products locally and internationally.
Nafion Modified Titanium Nitride pH Sensor for Future Biomedical Applications
Authors: Shylendra Shimrith Paul , Wajrak Magdalena , Alameh Kamal , Kang James Jin
Published: January 2023

pH sensors are increasingly being utilized in the biomedical field and have been implicated in health applications that aim to improve the monitoring and treatment of patients. In this work, a previously developed Titanium Nitride (TiN) solid-state pH sensor is further enhanced, with the potential to be used for pH regulation inside the human body and for other biomedical, industrial, and environmental applications. One of the main limitations of existing solid-state pH sensors is their reduced performance in high redox mediums. The potential shift E0 value of the previously developed TiN pH electrode in the presence of oxidizing or reducing agents is 30 mV. To minimize this redox shift, a Nafion-modified TiN electrode was developed, tested, and evaluated in various mediums. The Nafion-modified electrode has been shown to shift the E0 value by only 2 mV, providing increased accuracy in highly redox samples while maintaining acceptable reaction times. Overcoming the redox interference for pH measurement enables several advantages of the Nafion-modified TiN electrode over the standard pH glass electrode, implicating its use in medical diagnosis, real-time health monitoring, and further development of miniaturized smart sensors.
Robust Motor Imagery Tasks Classification Approach Using Bayesian Neural Network
Authors: Milanés-Hermosilla Daily , Trujillo-Codorniú Rafael , Lamar-Carbonell Saddid , Sagaró-Zamora Roberto , Tamayo-Pacheco Jorge Jadid , Villarejo-Mayor John Jairo , Delisle-Rodriguez Denis
Published: January 2023

The development of Brain–Computer Interfaces based on Motor Imagery (MI) tasks is a relevant research topic worldwide. The design of accurate and reliable BCI systems remains a challenge, mainly in terms of increasing performance and usability. Classifiers based on Bayesian Neural Networks are proposed in this work by using the variational inference, aiming to analyze the uncertainty during the MI prediction. An adaptive threshold scheme is proposed here for MI classification with a reject option, and its performance on both datasets 2a and 2b from BCI Competition IV is compared with other approaches based on thresholds. The results using subject-specific and non-subject-specific training strategies are encouraging. From the uncertainty analysis, considerations for reducing computational cost are proposed for future work.
A Novel System to Increase Yield of Manufacturing Test of an RF Transceiver through Application of Machine Learning
Authors: Siddiqui Atif , Otero Pablo , Zubair Muhammad
Published: January 2023

Electronic manufacturing and design companies maintain test sites for a range of products. These products are designed according to the end-user requirements. The end user requirement, then, determines which of the proof of design and manufacturing tests are needed. Test sites are designed to carry out two things, i.e., proof of design and manufacturing tests. The team responsible for designing test sites considers several parameters like deployment cost, test time, test coverage, etc. In this study, an automated test site using a supervised machine learning algorithm for testing an ultra-high frequency (UHF) transceiver is presented. The test site is designed in three steps. Firstly, an initial manual test site is designed. Secondly, the manual design is upgraded into a fully automated test site. And finally supervised machine learning is applied to the automated design to further enhance the capability. The manual test site setup is required to streamline the test sequence and validate the control and measurements taken from the test equipment and unit under test (UUT) performance. The manual test results showed a high test time, and some inconsistencies were observed when the test operator was required to change component values to tune the UUT. There was also a sudden increase in the UUT quantities and so, to cater for this, the test site is upgraded to an automated test site while the issue of inconsistencies is resolved through the application of machine learning. The automated test site significantly reduced test time per UUT. To support the test operator in selecting the correct component value the first time, a supervised machine learning algorithm is applied. The results show an overall improvement in terms of reduced test time, increased consistency, and improved quality through automation and machine learning.
Air Pollution and Radiation Monitoring in Collective Protection Facilities
Authors: Kołacz Angelika Monika , Wiśnik-Sawka Monika , Maziejuk Mirosław , Natora Marek , Harmata Władyslaw , Rytel Paweł , Gajda Dorota
Published: January 2023

It has become increasingly important to monitor environment contamination by such chemicals as chemical warfare agents (CWAs) and industrial toxic chemicals (TICs), as well as radiation hazards around and inside collective protection facilities. This is especially important given the increased risk of terrorist or military attacks. The Military Institute of Chemistry and Radiometry (MICR) has constructed and developed the ALERT device for the effective monitoring of these threats. This device uses sensors that detect chemical and radiological contaminations in the air. The CWA detector is an ion mobility spectrometer, TICs are detected by electrochemical sensors, and radiation hazards are detected via Geiger–Muller tubes. The system was designed to protect the crew from contamination. When chemical or radioactive contamination is detected at the air inlet for the shelter, air filtration through a carbon filter is activated. At this time, the air test procedure at the filter outlet is started to test the condition of the filter on an ongoing basis. After detecting contamination at the filter outlet, the system turns off the air pumping and the service can start the procedure of replacing the damaged carbon filter. This paper presents the results of laboratory testing of the ALERT gas alarm detector, which showed high measurements for important parameters, including sensitivity, repeatability, accuracy, and speed.
Perspectives of Motor Functional Upper Extremity Recovery with the Use of Immersive Virtual Reality in Stroke Patients
Authors: Sip Paweł , Kozłowska Marta , Czysz Dariusz , Daroszewski Przemysław , Lisiński Przemysław
Published: January 2023

Stroke is one of the leading causes of disability, including loss of hand manipulative skills. It constitutes a major limitation in independence and the ability to perform everyday tasks. Among the numerous accessible physiotherapeutic methods, it is becoming more common to apply Virtual Reality "VR”. The aim of this study was to establish whether immersive VR was worth considering as a form of physical therapy and the advisability of applying it in restoring post-stroke hand function impairment. A proprietary application Virtual Mirror Hand 1.0 was used in the research and its effectiveness in therapy was compared to classical mirror therapy. A total of 20 survivors after ischaemic stroke with comparable functional status were divided into a study group (n = 10) and control group (n = 10). Diagnostic tools included 36-Item Short Form Survey “SF-36” and the Fugl-Meyer Assessment Upper Extremity “FMA-UE”. Collected metrics showed a normal distribution and the differences in mean values were tested by the student’s t-test. In both, the study and control groups’ changes were recorded. A statistically significant outcome for FMA-UE and SF-36 measured by the student’s t-test for dependent or independent samples (p > 0.05) were obtained in both groups. Importantly, proven by conducted studies, an advantage of VR proprietary application was subjective sensations amelioration in pain and sensory impressions. Applying Virtual Mirror Hand 1.0 treatment to patients after a stroke appears to be a good solution and definitely provides the opportunity to consider VR applications as an integral part of the neurorehabilitation process. These results give a basis to plan further larger-scale observation attempts. Moreover, the development of the Virtual Mirror Hand 1.0 as an innovative application in physiotherapy may become equivalent to classical mirror therapy in improving the quality and effectiveness of the treatment used for post-stroke patients.
Angle-Only Cooperative Orbit Determination Considering Attitude Uncertainty
Authors: Shi Yishuai , Wang Junkui , Liu Chuankai , Wang Yangjun , Xu Qingchao , Zhou Xingyu
Published: January 2023

In this paper, a novel concept for cooperative orbit determination (OD) using inter-spacecraft angle-only measurements is proposed. Different from the conventional cooperative OD that only estimates orbit states, the attitude of the observer spacecraft is considered by incorporating the attitude into the estimated vector. The observability of a two-spacecraft system is analyzed based on the observability matrix. Observability analysis reveals that inter-spacecraft angle-only measurements are inadequate to estimate both the attitude and the orbit states in two-body dynamics. The observability of the two-spacecraft system can be improved by considering high-order gravitational perturbation or executing an attitude maneuver on the observer spacecraft. This is the first time that we present the observability analysis and orbit estimation results for a two-spacecraft system considering attitude uncertainty for the observer. Finally, simulation results demonstrate the effectiveness of the proposed method. The results in this paper can be potentially useful for autonomous managements of a spacecraft constellation and formation.
Analysis of Lidar Actuator System Influence on the Quality of Dense 3D Point Cloud Obtained with SLAM
Authors: Trybała Paweł , Szrek Jarosław , Dębogórski Błażej , Ziętek Bartłomiej , Blachowski Jan , Wodecki Jacek , Zimroz Radosław
Published: January 2023

Mobile mapping technologies, based on techniques such as simultaneous localization and mapping (SLAM) and surface-from-motion (SfM), are being vigorously developed both in the scientific community and in industry. They are crucial concepts for automated 3D surveying and autonomous vehicles. For various applications, rotating multiline scanners, manufactured, for example, by Velodyne and Ouster, are utilized as the main sensor of the mapping hardware system. However, their principle of operation has a substantial drawback, as their scanning pattern creates natural gaps between the scanning lines. In some models, the vertical lidar field of view can also be severely limited. To overcome these issues, more sensors could be employed, which would significantly increase the cost of the mapping system. Instead, some investigators have added a tilting or rotating motor to the lidar. Although the effectiveness of such a solution is usually clearly visible, its impact on the quality of the acquired 3D data has not yet been investigated. This paper presents an adjustable mapping system, which allows for switching between a stable, tilting or fully rotating lidar position. A simple experiment in a building corridor was performed, simulating the conditions of a mobile robot passing through a narrow tunnel: a common setting for applications, such as mining surveying or industrial facility inspection. A SLAM algorithm is utilized to create a coherent 3D point cloud of the mapped corridor for three settings of the sensor movement. The extent of improvement in the 3D data quality when using the tilting and rotating lidar, compared to keeping a stable position, is quantified. Different metrics are proposed to account for different aspects of the 3D data quality, such as completeness, density and geometry coherence. The ability of SLAM algorithms to faithfully represent selected objects appearing in the mapped scene is also examined. The results show that the fully rotating solution is optimal in terms of most of the metrics analyzed. However, the improvement observed from a horizontally mounted sensor to a tilting sensor was the most significant.
A New Evidence Weight Combination and Probability Allocation Method in Multi-Sensor Data Fusion
Authors: Ma Li , Yao Wenlong , Dai Xinguan , Jia Ronghao
Published: January 2023

A single sensor is prone to decline recognition accuracy in the face of a complex environment, while the existing multi-sensor evidence theory fusion methods do not comprehensively consider the impact of evidence conflict and fuzziness. In this paper, a new evidence weight combination and probability allocation method is proposed, which calculated the degree of evidence fuzziness through the maximum entropy principle, and also considered the impact of evidence conflict on fusing results. The two impact factors were combined to calculate the trusted discount and reallocate the probability function. Finally, Dempster’s combination rule was used to fuse every piece of evidence. On this basis, experiments were first conducted to prove that the existing weight combination methods produce results contrary to common sense when handling high-conflicting and high-clarity evidence, and then comparative experiments were conducted to prove the effectiveness of the proposed evidence weight combination and probability allocation method. Moreover, it was verified, on the PAMAP2 data set, that the proposed method can obtain higher fusing accuracy and more reliable fusing results in all kinds of behavior recognition. Compared with the traditional methods and the existing improved methods, the weight allocation method proposed in this paper dynamically adjusts the weight of fuzziness and conflict in the fusing process and improves the fusing accuracy by about 3.3% and 1.7% respectively which solved the limitations of the existing weight combination methods.
Static and Dynamic Accuracy and Occlusion Robustness of SteamVR Tracking 2.0 in Multi-Base Station Setups
Authors: Kuhlmann de Canaviri Lara , Meiszl Katharina , Hussein Vana , Abbassi Pegah , Mirraziroudsari Seyedeh Delaram , Hake Laurin , Potthast Tobias , Ratert Fabian , Schulten Tessa , Silberbach Marc , Warnecke Yannik , Wiswede Daniel , Schiprowski Witold , Heß Daniel , Brüngel Raphael , Friedrich Christoph M.
Published: January 2023

The tracking of objects and person position, orientation, and movement is relevant for various medical use cases, e.g., practical training of medical staff or patient rehabilitation. However, these demand high tracking accuracy and occlusion robustness. Expensive professional tracking systems fulfill these demands, however, cost-efficient and potentially adequate alternatives can be found in the gaming industry, e.g., SteamVR Tracking. This work presents an evaluation of SteamVR Tracking in its latest version 2.0 in two experimental setups, involving two and four base stations. Tracking accuracy, both static and dynamic, and occlusion robustness are investigated using a VIVE Tracker (3.0). A dynamic analysis further compares three different velocities. An error evaluation is performed using a Universal Robots UR10 robotic arm as ground-truth system under nonlaboratory conditions. Results are presented using the Root Mean Square Error. For static experiments, tracking errors in the submillimeter and subdegree range are achieved by both setups. Dynamic experiments achieved errors in the submillimeter range as well, yet tracking accuracy suffers from increasing velocity. Four base stations enable generally higher accuracy and robustness, especially in the dynamic experiments. Both setups enable adequate accuracy for diverse medical use cases. However, use cases demanding very high accuracy should primarily rely on SteamVR Tracking 2.0 with four base stations.
Torque Regulation Is Influenced by the Nature of the Isometric Contraction
Authors: Bauer Philipp , Gomes João Sá , Oliveira João , Santos Paulo , Pezarat-Correia Pedro , Vaz João R.
Published: January 2023

The present study aimed to investigate the effects of a continuous visual feedback and the isometric contraction nature on the complexity and variability of force. Thirteen healthy and young male adults performed three MVCs followed by three submaximal isometric force tasks at a target force of 40% of their MVC for 30 s, as follows: (i) push isometric task with visual feedback (Pvisual); (ii) hold isometric task with visual feedback (Hvisual); (iii) hold isometric task without visual feedback (Hnon-visual). Force complexity was evaluated through sample entropy (SampEn) of the force output. Force variability was analyzed through the coefficient of variation (CV). Results showed that differences were task-related, with Pvisual showing higher complexity (i.e., higher SampEn) and decreased variability (i.e., lower CV) when compared with the remaining tasks. Additionally, no significant differences were found between the two hold isometric force tasks (i.e., no influence of visual feedback). Our results are promising as we showed these two isometric tasks to induce different motor control strategies. Furthermore, we demonstrated that visual feedback’s influence is also dependent on the type of isometric task. These findings should motivate researchers and physiologists to shift training paradigms and incorporate different force control evaluation tasks.
Satellite Image Compression Guided by Regions of Interest
Authors: Schwartz Christofer , Sander Ingo , Bruhn Fredrik , Persson Mathias , Ekblad Joakim , Fuglesang Christer
Published: January 2023

Small satellites empower different applications for an affordable price. By dealing with a limited capacity for using instruments with high power consumption or high data-rate requirements, small satellite missions usually focus on specific monitoring and observation tasks. Considering that multispectral and hyperspectral sensors generate a significant amount of data subjected to communication channel impairments, bandwidth constraint is an important challenge in data transmission. That issue is addressed mainly by source and channel coding techniques aiming at an effective transmission. This paper targets a significant further bandwidth reduction by proposing an on-the-fly analysis on the satellite to decide which information is effectively useful before coding and transmitting. The images are tiled and classified using a set of detection algorithms after defining the least relevant content for general remote sensing applications. The methodology makes use of the red-band, green-band, blue-band, and near-infrared-band measurements to perform the classification of the content by managing a cloud detection algorithm, a change detection algorithm, and a vessel detection algorithm. Experiments for a set of typical scenarios of summer and winter days in Stockholm, Sweden, were conducted, and the results show that non-important content can be identified and discarded without compromising the predefined useful information for water and dry-land regions. For the evaluated images, only 22.3% of the information would need to be transmitted to the ground station to ensure the acquisition of all the important content, which illustrates the merits of the proposed method. Furthermore, the embedded platform’s constraints regarding processing time were analyzed by running the detection algorithms on Unibap’s iX10-100 space cloud platform.
Wideband Dual-Polarized Octagonal Cavity-Backed Antenna with Low Cross-Polarization and High Aperture Efficiency
Authors: Liu Yanxia , Isleifson Dustin , Shafai Lotfollah
Published: January 2023

Simultaneously enhancing multiple antenna performance parameters is a demanding task, especially with a challenging set of design goals. In this paper, by carefully deriving a compatible set of enhancement techniques, we propose a compact/lightweight/low-cost high-performance L-band octagonal cavity-backed hybrid antenna with multiple attractive features: dual-polarization, wide impedance bandwidth, low cross-polarization, high gain, and high aperture efficiency. The ground cavity is octagonal, which allows the antenna to have a small footprint, and, more importantly, low cross-polarization and high aperture efficiencies when compared to a commonly-used square design. The hybrid design relies on the resonance merging of two radiating elements, i.e., radiating feedlines and a conductive open prism, to form a wide impedance bandwidth. To permit polarization diversity and low cross-polarization, it is differentially and orthogonally fed. Herein, a series of parametric simulation studies on antenna configurations provide information on how to improve the impedance bandwidth and cross-polarization performance. To verify the simulation studies, an antenna prototype was fabricated and tested. Excellent agreement between the simulated and measured results was reached.
Sidelobe Suppression Techniques for Near-Field Multistatic SAR
Authors: Price George A. J. , Moate Chris , Andre Daniel , Yuen Peter
Published: January 2023

Multirotor Unmanned Air Systems (UAS) represent a significant improvement in capability for Synthetic Aperture Radar (SAR) imaging when compared to traditional, fixed-wing, platforms. In particular, a swarm of UAS can generate significant measurement diversity through variation of spatial and frequency collections across an array of sensors. In such imaging schemes, the image formation step is challenging due to strong extended sidelobe; however, were this to be effectively managed, a dramatic increase in image quality is theoretically possible. Since 2015, QinetiQ have developed the RIBI system, which uses multiple UAS to perform short-range multistatic collections, and this requires novel near-field processing to mitigate the high sidelobes observed and form actionable imagery. This paper applies a number of algorithms to assess image reconstruction of simulated near-field multistatic SAR with an aim to suppress sidelobes observed in the RIBI system, investigating techniques including traditional SAR processing, regularised linear regression, compressive sensing. In these simulations presented, Elastic net, Orthogonal Matched Pursuit, and Iterative Hard Thresholding all show the ability to suppress sidelobes while preserving accuracy of scatterer RCS. This has also lead to a novel processing approach for reconstructing SAR images based on the observed Elastic net and Iterative Hard Thresholding performance, mitigating weaknesses to generate an improved combined approach. The relative strengths and weaknesses of the algorithms are discussed, as well as their application to more complex real-world imagery.
Convolutional Neural Networks or Vision Transformers: Who Will Win the Race for Action Recognitions in Visual Data?
Authors: Moutik Oumaima , Sekkat Hiba , Tigani Smail , Chehri Abdellah , Saadane Rachid , Tchakoucht Taha Ait , Paul Anand
Published: January 2023

Understanding actions in videos remains a significant challenge in computer vision, which has been the subject of several pieces of research in the last decades. Convolutional neural networks (CNN) are a significant component of this topic and play a crucial role in the renown of Deep Learning. Inspired by the human vision system, CNN has been applied to visual data exploitation and has solved various challenges in various computer vision tasks and video/image analysis, including action recognition (AR). However, not long ago, along with the achievement of the transformer in natural language processing (NLP), it began to set new trends in vision tasks, which has created a discussion around whether the Vision Transformer models (ViT) will replace CNN in action recognition in video clips. This paper conducts this trending topic in detail, the study of CNN and Transformer for Action Recognition separately and a comparative study of the accuracy-complexity trade-off. Finally, based on the performance analysis’s outcome, the question of whether CNN or Vision Transformers will win the race will be discussed.
Interface Design of Head-Worn Display Application on Condition Monitoring in Aviation
Authors: Zhang Xiaoyan , Cheng Jia’ao , Xue Hongjun , Chen Siyu
Published: January 2023

Head-worn displays (HWDs) as timely condition monitoring are increasingly used in aviation. However, interface design characteristics that mainly affect HWD use have not been fully investigated. The aim of this study was to examine the effects of several important interface design characteristics (i.e., the distance between calibration lines and the layouts of vertical and horizontal scale belts) on task performance and user preference between different conditions of display, i.e., HWD or head-up display (HUD). Thirty participants joined an experiment in which they performed flight tasks. In the experiment, the calibration lines’ distance was set to three different levels (7, 9 and 11 mrad), and the scale belt layouts included horizontal and vertical scale belt layouts. The scale belts were set as follows: the original vertical scale belt width was set as L, and the horizontal scale belt height as H. The three layouts of the vertical calibration scale belt used were 3/4H, H and 3H/2. Three layouts of horizontal calibration scale belts were selected as 3L/4, L and 3L/2. The results indicated that participants did better with the HWD compared to the HUD. Both layouts of vertical and horizontal scale belts yielded significant effects on the users’ task performance and preference. Users showed the best task performance while the vertical calibration scale belts were set as H and horizontal calibration scale belts were set as L, and users generally preferred interface design characteristics that could yield an optimal performance. These findings could facilitate the optimal design of usable head-worn-display technology.
Calculation of Heartbeat Rate and SpO2 Parameters Using a Smartphone Camera: Analysis and Testing
Authors: Antoniou Panayiotis , Nestoros Marios , Polycarpou Anastasis C.
Published: January 2023

Mathematical and signal-processing methods were used to obtain reliable measurements of the heartbeat pulse rate and information on oxygen concentration in the blood using short video recordings of the index finger attached to a smartphone built-in camera. Various types of smartphones were used with different operating systems (e.g., iOS, Android) and capabilities. A range of processing algorithms were applied to the red-green-blue (RGB) component signals, including mean intensity calculation, moving average smoothing, and quadratic filtering based on the Savitzky–Golay filter. Two approaches—gradient and local maximum methods—were used to determine the pulse rate, which provided similar results. A fast Fourier transform was applied to the signal to correlate the signal’s frequency components with the pulse rate. We resolved the signal into its DC and AC components to calculate the ratio-of-ratios of the AC and DC components of the red and green signals, a method which is often used to estimate the oxygen concentration in blood. A series of measurements were performed on healthy human subjects, producing reliable data that compared favorably to benchmark data obtained by commercial and medically approved oximeters. Furthermore, the effect of the video recording duration on the accuracy of the results was investigated.
Synchronous Control of a Group of Flying Robots Following a Leader UAV in an Unfamiliar Environment
Authors: Wojtowicz Konrad , Wojciechowski Przemysław
Published: January 2023

An increasing number of professional drone flights require situational awareness of aerial vehicles. Vehicles in a group of drones must be aware of their surroundings and the other group members. The amount of data to be exchanged and the total cost are skyrocketing. This paper presents an implementation and assessment of an organized drone group comprising a fully aware leader and much less expensive followers. The solution achieved a significant cost reduction by decreasing the number of sensors onboard followers and improving the organization and manageability of the group in the system. In this project, a group of quadrotor drones was evaluated. An automatically flying leader was followed by drones equipped with low-end cameras only. The followers were tasked with following ArUco markers mounted on a preceding drone. Several test tasks were designed and conducted. Finally, the presented system proved appropriate for slowly moving groups of drones.
Multiport Single Element Mimo Antenna Systems: A Review
Authors: Sheriff Nathirulla , Kamal Abdul Rahim Sharul , Tariq Chattha Hassan , Kim Geok Tan
Published: January 2023

In response to the increasing demand for voice, data, and multimedia applications, the next generation of wireless communication systems is projected to provide faster data rates and better service quality to customers. Techniques such as Multiple-Input–Multiple-Output (MIMO) and diversity are being studied and implemented to meet the needs of next-generation wireless communication systems. Embedding multiple antennas into the same antenna system is seen as a promising solution, which can improve both the system’s channel capacity and the communication link’s quality. However, for small handheld and portable devices, embedding many antennas into a single device in a small area and at the same time providing good isolation becomes a challenge. Hence, designing a shared antenna system with multiple feed ports with equivalent or better performance characteristics as compared to the approach of multiple antennas with multiple feed ports is a promising advantage which can reduce the size and cost of manufacturing. This paper intends to provide an in-depth review of different MIMO antenna designs with common radiators covering various antenna design aspects such as isolation techniques, gain, efficiency, envelope correlation coefficient, and size, etc. There is also a discussion of the mathematical concepts of MIMO and different isolation techniques, as well as a comparative analysis of different shared radiator antenna designs. The literature review shows that only very few antennas’ design with common radiator have been suggested in the available literature at present. Therefore, in this review paper, we have endeavored to study different antennas’ designs with common radiator. A comparison is provided of their performance improvement techniques in a holistic way so that it can lead to further develop the common radiator multiport antenna systems and realize the promising advantages they offer.
A Shorted Stub Loaded UWB Flexible Antenna for Small IoT Devices
Authors: Ali Esraa , Awan Wahaj , Alzaidi Mohammed , Alzahrani Abdullah , Elkamchouchi Dalia , Falcone Francisco , Ghoneim Sherif
Published: January 2023

In this manuscript, a compact in size yet geometrically simple Ultra-Wideband (UWB) antenna is demonstrated. The flexible-by-nature substrate ROGERS 5880, having a thickness of 0.254 mm, is utilized to design the proposed work. The antenna configuration is an excerpt of a traditional rectangular monopole antenna resonating at 5 GHz. Initially, a pair of triangular slots are employed to extend the impedance bandwidth of the antenna. In addition, a semi-circular-shaped, short-ended stub is connected at the upper edges of the patch to further increase the operational bandwidth. After optimization, the proposed antenna offers UWB ranging from 2.73–9.68 GHz, covering almost the entire spectrum allocated globally for UWB applications. Further, the antenna offers a compact size of 15 × 20 mm2 that can easily be integrated into small, flexible electronics. The flexibility analysis is done by bending the antenna on both the x and y axes. The antenna offers performance stability in terms of return loss, radiation pattern, and gain for both conformal and non-conformal conditions. Furthermore, the strong comparison between simulated and measured results for both rigid and bent cases of the antenna, along with the performance comparison with the state-of-the-art, makes it a potential candidate for present and future compact-sized flexible devices.
Adaptive Aquila Optimizer Combining Niche Thought with Dispersed Chaotic Swarm
Authors: Zhang Yue , Xu Xiping , Zhang Ning , Zhang Kailin , Dong Weida , Li Xiaoyan
Published: January 2023

The Aquila Optimizer (AO) is a new bio-inspired meta-heuristic algorithm inspired by Aquila’s hunting behavior. Adaptive Aquila Optimizer Combining Niche Thought with Dispersed Chaotic Swarm (NCAAO) is proposed to address the problem that although the Aquila Optimizer (AO) has a strong global exploration capability, it has an insufficient local exploitation capability and a slow convergence rate. First, to improve the diversity of populations in the algorithm and the uniformity of distribution in the search space, DLCS chaotic mapping is used to generate the initial populations so that the algorithm is in a better exploration state. Then, to improve the search accuracy of the algorithm, an adaptive adjustment strategy of de-searching preferences is proposed. The exploration and development phases of the NCAAO algorithm are effectively balanced by changing the search threshold and introducing the position weight parameter to adaptively adjust the search process. Finally, the idea of small habitats is effectively used to promote the exchange of information between groups and accelerate the rapid convergence of groups to the optimal solution. To verify the optimization performance of the NCAAO algorithm, the improved algorithm was tested on 15 standard benchmark functions, the Wilcoxon rank sum test, and engineering optimization problems to test the optimization-seeking ability of the improved algorithm. The experimental results show that the NCAAO algorithm has better search performance and faster convergence speed compared with other intelligent algorithms.
Feature Ranking by Variational Dropout for Classification Using Thermograms from Diabetic Foot Ulcers
Authors: Hernandez-Guedes Abian , Arteaga-Marrero Natalia , Villa Enrique , Callico Gustavo M. , Ruiz-Alzola Juan
Published: January 2023

Diabetes mellitus presents a high prevalence around the world. A common and long-term derived complication is diabetic foot ulcers (DFUs), which have a global prevalence of roughly 6.3%, and a lifetime incidence of up to 34%. Infrared thermograms, covering the entire plantar aspect of both feet, can be employed to monitor the risk of developing a foot ulcer, because diabetic patients exhibit an abnormal pattern that may indicate a foot disorder. In this study, the publicly available INAOE dataset composed of thermogram images of healthy and diabetic subjects was employed to extract relevant features aiming to establish a set of state-of-the-art features that efficiently classify DFU. This database was extended and balanced by fusing it with private local thermograms from healthy volunteers and generating synthetic data via synthetic minority oversampling technique (SMOTE). State-of-the-art features were extracted using two classical approaches, LASSO and random forest, as well as two variational deep learning (DL)-based ones: concrete and variational dropout. Then, the most relevant features were detected and ranked. Subsequently, the extracted features were employed to classify subjects at risk of developing an ulcer using as reference a support vector machine (SVM) classifier with a fixed hyperparameter configuration to evaluate the robustness of the selected features. The new set of features extracted considerably differed from those currently considered state-of-the-art but provided a fair performance. Among the implemented extraction approaches, the variational DL ones, particularly the concrete dropout, performed the best, reporting an F1 score of 90% using the aforementioned SVM classifier. In comparison with features previously considered as the state-of-the-art, approximately 15% better performance was achieved for classification.
Comparison of Digestion Methods Using Atomic Absorption Spectrometry for the Determination of Metal Levels in Plants
Authors: Bankaji Insaf , Kouki Rim , Dridi Nesrine , Ferreira Renata , Hidouri Saida , Duarte Bernardo , Sleimi Noomene , Caçador Isabel
Published: January 2023

Trace metal elements (TMEs) are among the most important types of pollutants in the environment. Therefore, a precise determination of these contaminants in several environmental components is required for the safety assurance of living organisms. Spectroscopic analysis is an efficient technique employed to detect and determine TME contents in numerous samples. Hence, to achieve reliable and accurate results when using spectroscopic analysis, samples should be carefully prepared. In the present study, the comparison of eight digestion methods of five vegetal samples was carried out to quantify Cd, Mn, Al and Mg contents using the atomic absorption spectroscopy technique. According to the extraction techniques used in this study, results showed an outstanding difference in TME levels determined in the same vegetal sample. The results obtained indicated that the highest Mn concentrations were recorded when using the mixture of HNO3-HClO4 in the studied species: atriplex portulacoides, arthrocnemum indicum, olea europaea BCR-62, ulva lactuca and ulva lactuca BCR-279 compared to all other methods. Regarding the extraction of Cd, our results showed that heated extraction using different acids (HNO3-H2SO4-HClO4, HCl-HNO3, HNO3-HClO4, HNO3-H2SO4, HNO3-HCl-HClO4 and HNO3-HCl-H2SO4) was the most efficient in atriplex portulacoides, arthrocnemum indicum, olea europaea BCR-62, ulva lactuca and ulva lactuca BCR-279. Similarly, these heated acid digestion techniques (efficient for Cd) showed the highest levels of Al in atriplex portulacoides and arthrocnemum indicum. However, for the Mg extraction, our results revealed that the effectiveness of the method used depended on the plant species studied. Regarding these findings, the efficiency of metal quantification by AAS depends on the digestion procedure, the metallic ion to determine and the plant species.
Maize Breeding for Low Nitrogen Inputs in Agriculture: Mechanisms Underlying the Tolerance to the Abiotic Stress
Authors: Santos Talles de Oliveira , Amaral Junior Antônio Teixeira do , Moulin Monique Moreira
Published: January 2023

Nitrogen (N) is essential for sustaining life on Earth and plays a vital role in plant growth and thus agricultural production. The excessive use of N fertilizers not only harms the economy, but also the environment. In the context of the environmental impacts caused by agriculture, global maize improvement programs aim to develop cultivars with high N-use efficiency (NUE) to reduce the use of N fertilizers. Since N is highly mobile in plants, NUE is related to numerous little-known morphophysiological and molecular mechanisms. In this review paper we present an overview of the morpho-physiological adaptations of shoot and root, molecular mechanisms involved in plant response to low nitrogen environment, and the genetic effects involved in the control of key traits for NUE. Some studies show that the efficiency of cultivars growing under low N is related to deep root architecture, more lateral roots (LR), and sparser branching of LR, resulting in lower metabolic costs. The NUE cultivars also exhibit more efficient photosynthesis, which affects plant growth under suboptimal nitrogen conditions. In this sense, obtaining superior genotypes for NUE can be achieved with the exploitation of heterosis, as non-additive effects are more important in the expression of traits associated with NUE.
Mapping Soil Parameters with Environmental Covariates and Land Cover Projection in Tropical Rainforest, Hangadi Watershed, Ethiopia
Authors: Tamiru Berhanu , Soromessa Teshome , Warkineh Bikila , Legese Gudina
Published: January 2023

Machine learning and geostatistics are efficient techniques for investigating the geographic distribution of soil properties. This study’s objectives were to assess soil fertility status, map the spatial variability of selected soil parameters and compare random forest with ordinary kriging. Soil samples were collected to analyze parameters: pH, cation exchange capacity (CEC) and organic carbon (OC) using systematic sampling. Some environmental covariates were used in the machine learning process: a digital elevation model (DEM) collected from USGS distributing shuttle radar topography mission data and a LULC map generated from a 30-year time series (1988–2018) of Landsat 8. Georeferenced samples were sent to Batu Soil Research Laboratory. pH, CEC and OC were mapped and status was determined using random forest and ordinary kriging. Random forest was more accurate with low mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (high R2). In random forest, pH varied between 5.03 and 5.76 and ordinary kriging pH ranged from 4.96 to 5.76. pH was greater in cultivated land. CEC and OC were higher in the forest. The higher pH in cultivated land was due to grass coverage and minimal tillage. The addition of organic matter and CEC to a forest may result in higher OC. Environmental covariates (topographic, bands, NDVI and LULC) were used to predict the gradients of pH, OC and CEC. For pH, OC and CEC, DEM was the most important predictor. CEC was high in low landscape, but low in high landscape positions. Low OC requires composting, fallow and organic fertilizers. Future research should include the remaining predictors: physiochemical and lithological data to improve the performance of random forest.
Nutritional Interventions and Lifestyle Changing in Gestational Diabetes Mellitus Prevention: A Narrative Review
Authors: Zugravu Corina , Petra Andreea , Pietroșel Valeria-Anca , Mihai Bianca-Margareta , Mihai Doina-Andrada , Bohîlțea Roxana-Elena , Tarcea Monica
Published: January 2023

Background: Gestational diabetes mellitus (GDM) is the most common pregnancy complication, and its prevalence is increasing, as obesity is more prevalent in women at reproductive age. Food choices and patterns that might reduce incidence are of great importance, and the present review aims to offer a perspective on different types of nutritional interventions in GDM prevention. Methods: A literature review in the PubMed database was conducted in order to identify full-text, English, randomized control trials and observational clinical studies, published in the last 10 years, that are the most relevant to emphasize the usefulness of nutritional and lifestyle interventions in prevention of GDM. Results and discussions: Twenty-two articles met the inclusion criteria and were relevant for the search. Their outcomes were reported and analyzed. Dietary interventions were very heterogeneous, including general counselling of healthier eating patterns, recommendations to follow a Mediterranean dietary pattern or to choose low-glycemic-index foods, and dietary advice focusing on increasing consumption of some food groups or vitamin D or probiotics supplementations. Conclusions: Among these interventions, a moderate-intensity lifestyle intervention optimizing participants’ consumption of whole grains, vegetables, and fruits; portion control; lowering intake of ultra-processed food and simple sugars; and Mediterranean diet intervention were the most successful in reducing GDM incidence.
How Does Information and Communication Technology Affect Geothermal Energy Sustainability?
Authors: Alsaleh Mohd , Wang Xiaohui
Published: January 2023

There are many advantages of geothermal energy, as an environmentally friendly resource, with some other problems to be addressed before the full potential of this sustainable and renewable resource, which is natural, could be harnessed. This research will aim to examine what effect ICT, that is, information and communication technology factors with sustainability in the economy, has on geothermal energy output among the considered 27 EU nations within the time frame 1990 to 2021. The novelty of this research is the ability to clarify the role of ICT toward geothermal power sustainability in the EU27 region. As well as the magnitude of effects of ICT on the geothermal power sustainability in EU13 developing countries and EU14 developed countries using the ARDL estimator. Autoregressive distributed lag (ARDL) was adopted, and the findings show that a significant increase in the geothermal energy industry sustainability can occur in EU14 emerged economies using ICT factors than among the 13 emerging economies. Among additional factors, human capital, economic sustainability, and institutional quality contribute more positively to geothermal energy sustainability in EU14 emerging economies than in EU13 emerging economies. Similarly, further results show that a remarkable decrease in carbon dioxide emissions can occur in EU13 emerging economies using geothermal energy output than in EU14 emerged economies. All these results outputs are an indication that geothermal power sustainability among the European Union countries could be remarkably boosted by increasing the level of ICT determinants to attain the 2030 energy union goals. This study recommends that the considered European countries should prioritize the good functionality of ICT indicators in attaining societal objectives and that of the environment as well.