bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of Hydrogen Production System-Based PEM EL: PEM EL Modeling, DC/DC Power Converter, and Controller Design Approaches
Authors: Koundi Mohamed , El Fadil Hassan , EL Idrissi Zakaria , Lassioui Abdellah , Intidam Abdessamad , Bouanou Tasnime , Nady Soukaina , Rachid Aziz
Published: April 2023

The main component of the hydrogen production system is the electrolyzer (EL), which is used to convert electrical energy and water into hydrogen and oxygen. The power converter supplies the EL, and the controller is used to ensure the global stability and safety of the overall system. This review aims to investigate and analyze each one of these components: Proton Exchange Membrane Electrolyzer (PEM EL) electrical modeling, DC/DC power converters, and control approaches. To achieve this desired result, a review of the literature survey and an investigation of the PEM EL electrical modeling of the empirical and semi-empirical, including the static and dynamic models, are carried out. In addition, other sub-models used to predict the temperature, gas flow rates (H2 and O2), hydrogen pressure, and energy efficiency for PEM EL are covered. DC/DC power converters suitable for PEM EL are discussed in terms of efficiency, current ripple, voltage ratio, and their ability to operate in the case of power switch failure. This review involves analysis and investigation of PEM EL control strategies and approaches previously used to achieve control objectives, robustness, and reliability in studying the DC/DC converter-PEM electrolyzer system. The paper also highlights the online parameter identification of the PEM electrolyzer model and adaptive control issues. Finally, a discussion of the results is developed to emphasize the strengths, weaknesses, and imperfections of the literature on this subject as well as proposing ideas and challenges for future work.
Fabrication of a Composite Film Optic with High Transmittance in Vis and IR Regions for an Optical System
Authors: Yin Jiajia , Fan Bin , Du Junfeng , Yang Hu , Bian Jiang
Published: April 2023

In this study, a lightweight composite polyimide film optic with antireflective coating was prepared using an ion-beam-assisted reactive sputtering method. It exhibited high transmittance in visible (87%, 0.5~0.8 μm), short (86%, 1.8~2.7 μm) and middle (78%, 3.3~5.4 μm) wavelength infrared regions. Additionally, it also showed great optical homogeneity (0.006 λ in RMS and 0.034 λ in PV, λ = 632.8 nm) with smooth surfaces (RMS = 0.786 nm). The thermal stability of the polyimide film was also effectively maintained after the antireflective coating. At the same time, by utilizing the hydrophobic properties of coating materials (Ta2O5/SiO2), the antireflective layer acted as an effective water barrier on the film surface to reduce the water absorption.
Optimization and Characterization of Centrifugal-Cast Functionally Graded Al-SiC Composite Using Response Surface Methodology and Grey Relational Analysis
Authors: Saleh Bassiouny , Fathi Reham , Abdalla Modawy Adam Ali , Radhika N. , Ma Aibin , Jiang Jinghua
Published: April 2023

In this study, an optimization approach was employed to determine the optimal main parameters that improve the performance of functionally graded composites manufactured using a combination of stirring and horizontal centrifugal casting. Pure aluminum reinforced with silicon carbide particles was used as the material for the composites. The effects of key input parameters such as mold speed, pouring temperature, stirring speed, and radial distance were optimized using a combination of grey relational analysis and response surface methodology. The statistical significance of the predicted grey relational grade model was assessed through an analysis of variance to identify the appropriate main parameters. The results showed that radial distance had the greatest impact on the performance of the composites, followed by pouring temperature. The optimal combination of main parameters was determined to be a mold speed of 1000 rpm, a pouring temperature of 750 °C, a stirring speed of 150 rpm, and a radial distance of 1 mm. Confirmation tests using these optimal values resulted in a 54.69% improvement in the grey relational grade.
Synthesis of CaCO3-Based Hyperdispersants and Their Application in Aqueous Coatings
Authors: Bai Jue , Li Yu
Published: April 2023

As an essential pigment particle in white water-based coatings, light calcium carbonate (CaCO3) is difficult to disperse in water-based systems. The hard-to-disperse particles agglomerate, causing the viscosity of the coating to rise, which in turn affects the quality of the coating. Therefore, in order to obtain efficient dispersion, the hyperdispersant SSS–MPEGA–DMAEA (SMD) has been prepared in this study using sodium styrene sulfonate (SSS), polyethylene glycol monomethyl ether acrylate (MPEGA), and dimethylaminoethyl acrylate (DMAEA) as monomers through aqueous solution polymerization. Firstly, we utilized the central composite design method to conduct mathematical modeling of the monomer ratios so as to optimize the dispersion performance of the hyperdispersants. Secondly, the structural characteristics and molecular weight distribution of SMD were characterized by 1H NMR spectroscopy and GPC. Then, the effect of SMD on the dispersion of the CaCO3 slurry was investigated through particle size distribution and TEM measurements. Finally, we applied the SMD in aqueous white coatings and tested the surface properties of the paint film by SEM as well as the stability of the paint film. The results showed that SMD can significantly reduce the viscosity and particle size of the CaCO3 slurry. The waterborne coatings prepared by SMD had good storage stability and corrosion resistance, so the materials owned broad application prospects.
Matrices of Native and Oxidized Pectin and Ferrous Bisglycinate and Their In Vitro Behavior through Gastrointestinal Conditions
Authors: Jimenez Martin , Viteri Daniela , Oña Daniela , Leon Marco , Ochoa-Herrera Valeria , Carpintero Natalia , Sepulcre Francesc , Alvarez-Barreto Jose F.
Published: April 2023

Colloidal matrices of native and oxidized pectin were developed to improve iron bioavailability through the digestive tract. Ferrous bisglycinate (Gly-Fe), obtained by precipitation of glycine chelation to Fe2+, was mixed with native and peroxide-oxidized citrus pectin, and subsequently lyophilized. Controls included matrices with iron and glycine without chelation. The resulting samples were characterized through FTIR, SEM, and TGA/DSC before and after in vitro digestion, which was performed in simulated salivary, gastric, and intestinal fluids. During these digestions, swelling capacity and iron release were assessed. All matrix formulations were porous, and while pectin oxidation did not alter architecture, it changed their properties, increasing thermal stability, likely due to greater number of interaction possibilities through carbonyl groups generated during oxidation. This also resulted in lower swelling capacity, with greater stability observed when using the chelated complex. Higher swelling was found in gastric and intestinal fluids. Pectin oxidation also increased retention of the chelated form, contrary to what was observed with unchelated iron. Thus, there is an important effect of pectin oxidation combined with iron in the form of ferrous biglyscinate on matrix stability and iron release through the digestive tract. These matrices could potentially improve iron bioavailability, diminishing organoleptic changes in fortified iron foods.
Rheology of Pickering Emulsions Stabilized and Thickened by Cellulose Nanocrystals over Broad Ranges of Oil and Nanocrystal Concentrations
Authors: Kinra Saumay , Pal Rajinder
Published: April 2023

The rheology of oil-in-water (O/W) emulsions, stabilized and thickened by cellulose nanocrystals, also referred to as nanocrystalline cellulose (NCC), was investigated over broad ranges of NCC and oil concentrations. The NCC concentration was varied from 1.03 to 7.41 wt% based on the aqueous phase. The oil concentration of the emulsion was varied from approximately 10 to 70 wt%. The emulsions produced were highly stable with respect to creaming and coalescence. The emulsions were non-Newtonian in that they exhibited strong shear-thinning behavior. The rheological data were described adequately by a power-law model. The consistency index (K) and the flow behavior index (n) of the emulsions were strongly dependent on the NCC and oil concentrations. At a fixed oil concentration, the consistency index increased whereas the flow behavior index decreased with the increase in NCC concentration. A similar behavior was observed when the NCC concentration was fixed and the oil concentration was increased; that is, the consistency index increased whereas the flow behavior index decreased.
Superconducting Stiffness and Coherence Length of FeSe0.5Te0.5 Measured in a Zero-Applied Field
Authors: Peri Amotz , Mangel Itay , Keren Amit
Published: April 2023

Superconducting stiffness ρs and coherence length ξ are usually determined by measuring the penetration depth λ of a magnetic field and the upper critical field Hc2 of a superconductor (SC), respectively. However, in magnetic SC, which is iron-based, this could lead to erroneous results, since the internal field could be very different from the applied one. To overcome this problem in Fe1+ySexTe1−x with x∼0.5 and y∼0 (FST), we measured both quantities with the Stiffnessometer technique. In this technique, one applies a rotor-free vector potential A to a superconducting ring and measures the current density j via the ring’s magnetic moment m. ρs and ξ are determined from London’s equation, j=−ρsA, and its range of validity. This method is particularly accurate at temperatures close to the critical temperature Tc. We find weaker ρs and longer ξ than existing literature reports, and critical exponents which agree better with expectations based on the Ginzburg–Landau theory.
Material and Environmental Aspects of Concrete Flooring in Cold Climate
Authors: Nilimaa Jonny , Zhaka Vasiola
Published: April 2023

Dehydration of concrete floor slabs is a critical step to ensure that the flooring material adheres properly and that there is no moisture-related damage to the floor after installation. Dehydration in a cold climate is often a slow process, which can have a big impact on the overall duration of the construction project, and corresponding measures are often taken to accelerate the drying process, especially in constructions exposed to a cold climate. One common method, typically used to accelerate dehydration in cold weather, is to introduce internal heating cables into the slab. This method reduces the dehydration time, but may not be the best solution from a sustainability perspective. This paper presents a concept study of concrete flooring in a cold climate from a cradle to practical completion perspective. The study focused on the environmental and material aspects of the dehydration of concrete floors in a cast-in-place house. This paper showed that concretes with high water-cement ratios, which are typically preferred due to their low CO2 emissions, may require measures for accelerated dehydration, which ultimately results in a higher environmental impact. The importance of environmental studies is also highlighted to fully understand the environmental aspects of construction.
Genetic Analysis and Epitope Prediction of SARS-CoV-2 Genome in Bahia, Brazil: An In Silico Analysis of First and Second Wave Genomics Diversity
Authors: Andrade Gabriela , Matias Guilherme , Chrisóstomo Lara , da Costa-Neto João , Sampaio Juan , Silva Arthur , Cansanção Isaac
Published: April 2023

COVID-19 is an infectious disease caused by SARS-CoV-2. This virus presents high levels of mutation and transmissibility, which contributed to the emergence of the pandemic. Our study aimed to analyze, in silico, the genomic diversity of SARS-CoV-2 strains in Bahia State by comparing patterns in variability of strains circulating in Brazil with the first isolated strain NC_045512 (reference sequence). Genomes were collected using GISAID, and subsequently aligned and compared using structural and functional genomic annotation. A total of 744 genomes were selected, and 20,773 mutations were found, most of which were of the SNP type. Most of the samples presented low mutational impact, and of the samples, the P.1 (360) lineage possessed the highest prevalence. The most prevalent epitopes were associated with the ORF1ab protein, and in addition to P.1, twenty-one other lineages were also detected during the study period, notably B.1.1.33 (78). The phylogenetic tree revealed that SARS-CoV-2 variants isolated from Bahia were clustered closely together. It is expected that the data collected will help provide a better epidemiological understanding of the COVID-19 pandemic (especially in Bahia), as well as helping to develop more effective vaccines that allow less immunogenic escape.
CanDiag: Fog Empowered Transfer Deep Learning Based Approach for Cancer Diagnosis
Authors: Pati Abhilash , Parhi Manoranjan , Pattanayak Binod Kumar , Sahu Bibhuprasad , Khasim Syed
Published: April 2023

Breast cancer poses the greatest long-term health risk to women worldwide, in both industrialized and developing nations. Early detection of breast cancer allows for treatment to begin before the disease has a chance to spread to other parts of the body. The Internet of Things (IoT) allows for automated analysis and classification of medical pictures, allowing for quicker and more effective data processing. Nevertheless, Fog computing principles should be used instead of Cloud computing concepts alone to provide rapid responses while still meeting the requirements for low latency, energy consumption, security, and privacy. In this paper, we present CanDiag, an approach to cancer diagnosis based on Transfer Deep Learning (TDL) that makes use of Fog computing. This paper details an automated, real-time approach to diagnosing breast cancer using deep learning (DL) and mammography pictures from the Mammographic Image Analysis Society (MIAS) library. To obtain better prediction results, transfer learning (TL) techniques such as GoogleNet, ResNet50, ResNet101, InceptionV3, AlexNet, VGG16, and VGG19 were combined with the well-known DL approach of the convolutional neural network (CNN). The feature reduction technique principal component analysis (PCA) and the classifier support vector machine (SVM) were also applied with these TDLs. Detailed simulations were run to assess seven performance and seven network metrics to prove the viability of the proposed approach. This study on an enormous dataset of mammography images categorized as normal and abnormal, respectively, achieved an accuracy, MCR, precision, sensitivity, specificity, f1-score, and MCC of 99.01%, 0.99%, 98.89%, 99.86%, 95.85%, 99.37%, and 97.02%, outperforming some previous studies based on mammography images. It can be shown from the trials that the inclusion of the Fog computing concepts empowers the system by reducing the load on centralized servers, increasing productivity, and maintaining the security and integrity of patient data.
SDS Electrophoresis on Gradient Polyacrylamide Gels as a Semiquantitative Tool for the Evaluation of Proteinuria
Authors: Mazur Paulina , Dumnicka Paulina , Tisończyk Joanna , Ząbek-Adamska Anna , Drożdż Ryszard
Published: April 2023

Proteinuria is an important sign of kidney diseases. Different protein patterns in urine associated with glomerular, tubular and overload proteinuria may be differentiated using the immunochemical detection of indicator proteins or via urinary proteins electrophoresis. Our aim was to characterize sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS-PAGE) using commercially available 4–20% gradient gels as a method to detect and differentiate proteinuria. Our laboratory-based study used excess urine samples collected for routine diagnostic purposes from adult patients of a tertiary-care hospital, including patients with albumin/creatinine < 30 mg/g and patients with dipstick proteinuria. The limit of albumin detection was estimated to be 3 mg/L. In 93 samples with albumin/creatinine < 30 mg/g, an albumin fraction was detected in 87% of samples with a minimum albumin concentration of 2.11 mg/L. The separation of 300 urine samples of patients with proteinuria revealed distinct protein patterns differentiated using the molecular weights of the detected proteins: glomerular (albumin and higher molecular weights) and two types of tubular proteinuria (“upper” ≥20 kDa and “lower” with lower molecular weights). These patterns were associated with different values of the glomerular filtration rate (median 66, 71 and 31 mL/min/1.72 m2, respectively, p = 0.004) and different proportions of multiple myeloma and nephrological diagnoses. As confirmed using tandem mass spectrometry and western blot, the SDS-PAGE protein fractions contained indicator proteins including immunoglobulin G, transferrin (glomerular proteinuria), α1-microglobulin, retinol-binding protein, neutrophil gelatinase-associated lipocalin, cystatin C, and β2-microglobulin (tubular), immunoglobulin light chain, myoglobin, and lysozyme (overflow). SDS-PAGE separation of urine proteins on commercially available 4–20% gradient gels is a reliable technique to diagnose proteinuria and differentiate between its main clinically relevant types.
Camouflage Correction of Skeletal Class III Severe Open Bite with Tooth Ankylosis Treated by Temporary Anchorage Devices: A Case Report
Authors: Yashima Yuka , Kaku Masato , Yamamoto Taeko , Medina Cynthia Concepcion , Ono Shigehiro , Takeda Yosuke , Tanimoto Kotaro
Published: April 2023

Tooth ankylosis is a disorder characterized by the fusion of tooth and alveolar bone. This case report describes the treatment of a severe open bite due to tooth ankylosis. A 14-year-old female patient with a chief complaint of masticatory dysfunction was diagnosed with skeletal Class III severe anterior open bite and tooth ankylosis. She visited our university hospital with a chief complaint of an anterior open bite. After the surgical luxation of the ankylosed maxillary right central incisor, the tooth was orthodontically retracted using a nickel-titanium wire. The right mandibular lateral incisor and canine were luxated and retracted using intermaxillary elastics from a temporary anchorage device (TAD), which was inserted in the opposite jaw. During the treatment, skeletal Class III malocclusion deteriorated due to anterior growth of the mandible. Therefore, TADs were inserted into the retromolar pad on both sides of the mandible and retracted into the mandibular dental arch. Although the mandibular right canine was luxated several times, it could not be brought to the occlusal line, and was thus extracted; the extraction space was replaced with a prosthesis. Consequently, a normal overjet and overbite with a straight profile were achieved. Extrusion of ankylosed teeth by intermaxillary elastics from a TAD is a valid treatment option for patients with severe open bites.
A Dual Aircraft Maneuver Formation Controller for MAV/UAV Based on the Hybrid Intelligent Agent
Authors: Zhao Luodi , Liu Yemo , Peng Qiangqiang , Zhao Long
Published: April 2023

This paper proposes a hybrid intelligent agent controller (HIAC) for manned aerial vehicles (MAV)/unmanned aerial vehicles (UAV) formation under the leader–follower control strategy. Based on the high-fidelity three-degrees-of-freedom (DOF) dynamic model of UAV, this method decoupled multiple-input-multiple-output (MIMO) systems into multiple single-input-single-output (SISO) systems. Then, it innovatively combined the deep deterministic policy gradient (DDPG) and the double deep Q network (DDQN) to construct a hybrid reinforcement learning-agent model, which was used to generate onboard desired state commands. Finally, we adopted the dynamic inversion control law and the first-order lag filter to improve the actual flight-control process. Under the working conditions of a continuous S-shaped large overload maneuver for the MAV, the simulations verified that the UAV can achieve accurate tracking for the complex trajectory of the MAV. Compared with the traditional linear quadratic regulator (LQR) and DDPG, the HIAC has better control efficiency and precision.
Joint UAV Deployment and Task Offloading Scheme for Multi-UAV-Assisted Edge Computing
Authors: Li Fan , Luo Juan , Qiao Ying , Li Yaqun
Published: April 2023

With the development of the Internet of Things (IoT), IoT devices are increasingly being deployed in scenarios with large footprints, remote locations, and complex geographic environments. In these scenarios, base stations are usually not easily deployed and are easily destroyed, so unmanned aerial vehicle (UAV)-based edge computing is a good solution. However, the UAV cannot accomplish the computing tasks and efficiently achieve better resource allocation considering the limited communication and computing resources of the UAV. In this paper, a multi-UAV-assisted mobile edge computing (MEC) system is considered where multiple UAVs cooperate to provide a service to IoT devices. We formulate an optimization function to minimize the energy consumption of a multi-UAV-assisted MEC system. The optimization function is a complex problem with non-convex and multivariate coupling. Thus, a joint UAV deployment and task scheduling optimization algorithm are designed to achieve optimal values of UAV numbers, the hovering position of each UAV, and the best strategy for offloading and resource allocation. Experimental results demonstrate that the algorithm has positive convergence performance and can accomplish more tasks under the constraint of delay compared to the two benchmark algorithms. The proposed algorithm can effectively reduce the system energy consumption compared to the two state-of-the-art algorithms.
A Dynamic Checkpoint Interval Decision Algorithm for Live Migration-Based Drone-Recovery System
Authors: Kim Bongjae , Han Jungkyu , Jang Joonhyouk , Jung Jinman , Heo Junyoung , Min Hong , Rhee Dong Sop
Published: April 2023

Numerous services and applications have been developed to monitor anomalies or collect various sensing information in large-scale monitoring areas using drones. Nonetheless, interruptions of drone missions in such areas occasionally occur due to network errors, low battery levels, or physical defects, such as damage to the rotor and propeller. Checkpointing is a technique that periodically saves the system’s state, allowing it to be restored to that point in the event of a failure. In such circumstances, checkpointing techniques can be used to periodically save information related to the drone mission and replace a malfunctioning drone with the saved checkpoint information. In this paper, we propose a dynamic checkpoint interval decision algorithm for a live migration-based drone-recovery system. The proposed scheme minimizes the drone’s energy consumption while efficiently performing checkpointing. According to the basic experimental results, the proposed scheme consumed only about 3.51% more energy, while performing about 25.97% more checkpoint operations compared to the FIC (Fixed Interval Checkpointing) scheme. By using the proposed scheme, it is possible to increase the availability of checkpoint information and quickly resume drone missions, while minimizing the increase in energy consumption of the drone by saving checkpoints more frequently. Therefore, the proposed scheme can improve the reliability and stability of drone-based services.
Generation Change in Agriculture: A Systematic Review of the Literature
Authors: Borda Áron József , Sárvári Balázs , Balogh Jeremiás Máté
Published: April 2023

Today, the replacement of the ageing agricultural population is a global challenge in many food-producing countries. This article aims to provide an overview of generational change in agriculture based on the literature in international economics published in recent years, using a systematic review of the scientific literature. Research has identified several factors as barriers to agricultural generational change. Young people are less motivated to take over family farms. Farming does not offer them sufficient income, and the working conditions are not ideal. Access to land is severely limited worldwide, and the market bargaining power of the younger generation is low. Administrative burdens are also a barrier to the generational renewal of farms. The effects of climate change also have the potential to discourage next-generation farmers. Financial support for generational change in agriculture could be one solution to all these problems. Furthermore, generational change can be enhanced by the modernization of farms, providing farmers with access to land, and making a positive difference to their income, all of which will increase the motivation of young farmers.
The Journey to Making ‘Digital Technology’ Education a Community Learning Venture
Authors: Carroll Fiona , Faruque Rumana , Hewage Chaminda , Bentotahewa Vibhushinie , Meace Sophie
Published: April 2023

Technology has become an integral part of our educational systems, and its importance in our schools cannot be overstated. However, digital skills, unlike other literacy skills, such as reading, writing, and numeracy, still have many discontinuities between how children use them at home versus in school. Therefore, in Wales (UK), digital skills are being promoted as part of the Digital Competence Framework (DCF) and feature highly in the new Curriculum for Wales (2022). Moreover, the new Digital Technology General Certificate of Secondary Education (GCSE) in Wales has been introduced to provide learners with the opportunity to gain a qualification that builds digital skills, knowledge, and understanding. However, this also brings many challenges for teachers, such as a lack of confidence, knowledge, and training, as well as a lack of resources and fear of change, to name a few. These challenges, in turn, have an impact on pupils’ motivation and performance, as well as parents’ ability to support their children. This paper presents a qualitative case study on the development of a new digital technology learning community for primary and secondary school pupils, their teachers, and parents in Blaenau Gwent, Wales (UK). Firstly, the paper will provide insight into what was required to establish an effective learning community, including ensuring engagement and buy-in from all stakeholders. Secondly, through the description, analysis, and interpretation of findings from two studies, the paper will highlight the impact of the DTLSN learning community on teachers and pupils in Blaenau Gwent, especially in terms of their learning and teaching.
A Novel Automated Empirical Mode Decomposition (EMD) Based Method and Spectral Feature Extraction for Epilepsy EEG Signals Classification
Authors: Murariu Mădălina-Giorgiana , Dorobanțu Florica-Ramona , Tărniceriu Daniela
Published: April 2023

The increasing incidence of epilepsy has led to the need for automatic systems that can provide accurate diagnoses in order to improve the life quality of people suffering from this neurological disorder. This paper proposes a method to automatically classify epilepsy types using EEG recordings from two databases. This approach uses the spectral power density of intrinsic mode functions (IMFs) that are obtained through the empirical mode decomposition (EMD) of EEG signals. The spectral power density of IMFs has been applied as features for the classification of focal and non-focal, as well as of focal and generalized EEG signals. The data are then classified using K-nearest Neighbor (KNN) and Naïve Bayes (NB) classifiers. The focal and non-focal data were classified with high accuracy, with KNN and NB classifiers achieving a maximum classification rate of 99.90% and 99.80%, respectively. Focal and generalized epilepsy data were classified with high rates of accuracy during wakefulness and sleep stages, with KNN achieving a maximum rate of 99.49% and NB achieving 99.20%. This method shows significant improvements in the classification of EEG signals in epilepsy compared to previous studies. It could potentially aid clinical decisions for epilepsy patients.
Design and FPGA-Based Hardware Implementation of NB-IoT Physical Uplink Shared Channel Transmitter and Physical Downlink Shared Channel Receiver
Authors: Abostait Abdallah , Tawfik Rania M. , Darweesh M. Saeed , Mostafa Hassan
Published: April 2023

With the anticipated growth of the internet of things (IoT) market, many low-power wide-area (LPWA) technologies have been introduced to connect a wide range of IoT devices with varying performance requirements. The narrowband internet of things (NB-IoT) is a 3rd generation partnership project (3GPP) standardized LPWA technology that meets most IoT service requirements. In this paper, the design and implementation of the physical uplink transmitting chain as well as the physical downlink receiving chain of the NB-IoT user equipment (UE) are presented. Both chains’ main blocks are designed to follow the 3GPP NB-IoT LTE standard Release 14 (Rel-14). The whole design is experimentally implemented on the Virtex 7 (VC 709) Connectivity kit, and all performance metrics are reported. Moreover, an NB-IoT base station is implemented and integrated with the two prototyped UEs to set-up an NB-IoT system, which is employed to send data from one UE to another UE through the NB-IoT base station using two FPGAs (one to implement the sending UE and the other one to implement the receiving UE) and three universal software radio peripherals (USRPs) B200 (one to implement the RF front-end of the transmitting UE FPGA, one to implement the base station RF front-end, and one to implement the RF front-end of the receiving UE FPGA). Experimental results show that the implemented NB-IoT system is working successfully, as the two NB-IoT UEs communicate together successfully through the NB-IoT base station and exchange the data properly.
Distributed Anonymous e-Voting Method Based on Smart Contract Authentication
Authors: Tang Wenjie , Yang Wenzhong , Tian Xiaodan , Yuan Shaoqi
Published: April 2023

With the development of science and technology, the traditional centralized ballot management will lead to the risk of an opaque voting process and tampering of back-end data, and it can no longer meet the requirements of e-voting transparency and anonymity, while the distributed blockchain technology, with its features of being transparent and tamper-proof, can well solve the problems in traditional e-voting and make the ballot firmly in the hands of users. To make each node reach consensus, each node can access the complete shared ledger, and malicious nodes can analyze the transaction information in the ledger to obtain users’ voting information, which makes anonymity impossible to guarantee. We propose a blockchain technology-based voting record synchronization model and an anonymous authentication model, using zk-SNARK and Merkle tree technology, that achieve user authentication and anonymous voting. In this scheme, the user’s random identity address is inserted into the Merkle tree, and when voting, it is only necessary to prove that the user’s identity address is in the tree to complete anonymous voting without revealing the user’s real identity. This scheme meets the basic requirements of electronic voting and ensures the reliability and security of voting.
Discriminating WirelessHART Communication Devices Using Sub-Nyquist Stimulated Responses
Authors: Long Jeffrey D. , Temple Michael A. , Rondeau Christopher M.
Published: April 2023

Reliable detection of counterfeit electronic, electrical, and electromechanical devices within critical information and communications technology systems ensures that operational integrity and resiliency are maintained. Counterfeit detection extends the device’s service life that spans manufacture and pre-installation to removal and disposition activity. This is addressed here using Distinct Native Attribute (DNA) fingerprinting while considering the effects of sub-Nyquist sampling on DNA-based discrimination. The sub-Nyquist sampled signals were obtained using factor-of-205 decimation on Nyquist-compliant WirelessHART response signals. The DNA is extracted from actively stimulated responses of eight commercial WirelessHART adapters and metrics introduced to characterize classifier performance. Adverse effects of sub-Nyquist decimation on active DNA fingerprinting are first demonstrated using a Multiple Discriminant Analysis (MDA) classifier. Relative to Nyquist feature performance, MDA sub-Nyquist performance included decreases in classification of %CΔ ≈ 35.2% and counterfeit detection of %CDRΔ ≈ 36.9% at SNR = −9 dB. Benefits of Convolutional Neural Network (CNN) processing are demonstrated and include a majority of this degradation being recovered. This includes an increase of %CΔ ≈ 26.2% at SNR = −9 dB and average CNN counterfeit detection, precision, and recall rates all exceeding 90%.
DCEC: D2D-Enabled Cost-Aware Cooperative Caching in MEC Networks
Authors: Wu Jingyan , Zhang Jiawei , Ji Yuefeng
Published: April 2023

Various kinds of powerful intelligent mobile devices (MDs) need to access multimedia content anytime and anywhere, which places enormous pressure on mobile wireless networks. Fetching content from remote sources may introduce overly long accessing delays, which will result in a poor quality of experience (QoE). In this article, we considered the advantages of combining mobile/multi-access edge computing (MEC) with device-to-device (D2D) technologies. We propose a D2D-enabled cooperative edge caching (DCEC) architecture to reduce the delay of accessing content. We designed the DCEC caching management scheme through the maximization of a monotone submodular function under matroid constraints. The DCEC scheme includes a proactive cache placement algorithm and a reactive cache replacement algorithm. Thus, we obtained an optimal content caching and content update, which minimized the average delay cost of fetching content files. Finally, simulations compared the DCEC network architecture with the MEC and D2D networks and the DCEC caching management scheme with the least-frequently used and least-recently used scheme. The numerical results verified that the proposed DCEC scheme was effective at improving the cache hit ratio and the average delay cost. Therefore, the users’ QoE was improved.
Unsupervised Multi-Scale-Stage Content-Aware Homography Estimation
Authors: Hou Bin , Ren Jinlai , Yan Weiqing
Published: April 2023

Homography estimation is a critical component in many computer-vision tasks. However, most deep homography methods focus on extracting local features and ignore global features or the corresponding relationship between features from two images or video frames. These methods are effective for alignment of image pairs with small displacement. In this paper, we propose an unsupervised Multi-Scale-Stage Content-Aware Homography Estimation Network (MS2CA-HENet). In the framework, we use multi-scale input images for different stages to cope with different scales of transformations. In each stage, we consider local and global features via our Self-Attention-augmented ConvNet (SAC). Furthermore, feature matching is explicitly enhanced using feature-matching modules. By shrinking the error residual of each stage, our network achieves coarse-to-fine results. Experiments show that our MS2CA-HENet achieves better results than other methods.
A Review of Different Types of Solar Cell Materials Employed in Bifacial Solar Photovoltaic Panel
Authors: Vimala Muthu , Ramadas Geetha , Perarasi Muthaiya , Manokar Athikesavan Muthu , Sathyamurthy Ravishankar
Published: April 2023

Conventionally accessible silicon solar cells experience two major drawbacks, such as reduced efficiency and increased fabrication costs. The prospects for the reduction in the cost of the photovoltaic form of energy conversion are bifacial solar cells. Bifacial solar cells show potential opportunity in reducing the cost of solar energy conversion when analyzed with respect to monofacial cells. The bifacial solar cells exploit sunlight occurrence on both sides of the cell more efficiently. Bifacial-based solar photovoltaic (PV) is a technology that increases the generation of electrical energy per square meter of PV module through the utilization of light absorption from the albedo. This technology can generally be categorized based on the type of solar cell material and the fabrication technique. PV devices are classified as a silicon-based, thin film, organic, and advanced nano PV. This paper takes a second look at some recent initiatives and significant issues in enhancing the efficiency of bifacial solar cells from material sciences and chemical composition aspects. From this review, it is concluded that screen-printed solar cells have produced a maximum efficiency of 22%. Additionally, triode structure single-crystalline cells produced a maximum front side efficiency of 21.3% and rear side efficiency of 19.8%. Considering the recycling of solar panels, organic solar panels can be developed.
Study on the Effect of Initial Delamination on Tensile Behavior of Offshore Wind Turbine Blade Spar Cap
Authors: Xin Wen , Li Hui , Lu Xiaolong , Zhou Bo
Published: April 2023

Delamination damage to spar caps seriously endangers the operation safety of offshore wind turbines. The effect of initial delamination of various depths and areas on the ultimate tensile load of laminates is studied based on experiments and numerical simulation, and an effective method for predicting the residual tensile strength of laminates with high thickness is proposed. Three groups of initial delamination specimens with different characteristics were fabricated, and static displacement tensile tests were carried out. An accurate three-dimensional numerical analysis model was established, and the results were in good agreement with the experimental values, with the overall error of the failure load being less than 6%. Furthermore, a numerical model for a 20-ply high-thickness spar cap laminate was established to predict the effect of delamination on tensile strength. The results showed that, for the same depth of initial delamination, the difference in delamination area had little influence on the tensile strength. The dangerous locations of delamination were at the shallow surface and at the ratio of 0.3–0.4 in the thickness direction, and the maximum decrease in tensile strength was 14.86%; meanwhile, it was found that delamination on the middle surface had no significant effect on tensile strength.
Combustion of Lean Methane/Propane Mixtures with an Active Prechamber Engine in Terms of Various Fuel Distribution
Authors: Pielecha Ireneusz , Szwajca Filip
Published: April 2023

The possibilities for reducing the fuel consumption of internal combustion engines focus mainly on developing combustion systems, as one such solution is a two-stage combustion system using jet ignition. The combustion of gaseous mixtures with a high excess air ratio leads to an increase in overall efficiency and a reduction in the emissions of selected exhaust components. In such a convention, gas combustion studies were conducted in the methane/propane configuration. Using an active prechamber where spark plugs were placed and direct injection through a check valve, the fuel dose was minimized into the prechamber. The tests were conducted for a constant center of combustion (CoC). The combustion process in both the prechamber and main chamber was analyzed using a test stand equipped with a 0.5 dm3 single-cylinder engine. The engine was controlled by varying the fuel supply to the prechamber and main chamber in excess air ratio λ = 1.3–1.8. The study analyzed thermodynamic indices such as the combustion pressure in both chambers, based on which the SoC in both chambers, the rate and amount of heat released, AI05, AI90 and, consequently, the indicated efficiency were determined. Based on the results, it was found that the use of CH4/C3H8 combination degraded the thermodynamic indicators of combustion more than using only the base gas (methane). In addition, the stability of the engine’s operation was decreased. The advantage of using propane for the prechamber is to obtain more beneficial ecological indicators. For the single-fuel system, a maximum indicated efficiency of more than 40% was obtained, while with the use of propane for the prechamber, a maximum of 39.3% was achieved.
Revolutionizing Photovoltaic Systems: An Innovative Approach to Maximum Power Point Tracking Using Enhanced Dandelion Optimizer in Partial Shading Conditions
Authors: Halassa Elmamoune , Mazouz Lakhdar , Seghiour Abdellatif , Chouder Aissa , Silvestre Santiago
Published: April 2023

Partial shading (PS) is a prevalent phenomenon that often affects photovoltaic (PV) installations, leads to the appearance of numerous peaks in the power-voltage characteristics of PV cells, caused by the uneven distribution of solar irradiance on the PV module surface, known as global and local maximum power point (GMPP and LMPP). In this paper, a new technique for achieving GMPP based on the dandelion optimizer (DO) algorithm is proposed, inspired by the movement of dandelion seeds in the wind. The proposed technique aimed to enhance the efficiency of power generation in PV systems, particularly under PS conditions. However, the DO-based MPPT is compared with other advanced maximum power point tracker (MPPT) algorithms, such as Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Artificial Bee Colony (ABC), Cuckoo Search Algorithm (CSA), and Bat Algorithm (BA). Simulation results establish the superiority and effectiveness of the used MPPT in terms of tracking efficiency, speed, robustness, and simplicity of implementation. Additionally, these results reveal that the DO algorithm exhibits higher performance, with a root mean square error (RMSE) of 1.09 watts, a convergence time of 2.3 milliseconds, and mean absolute error (MAE) of 0.13 watts.
Establishment of Austria’s First Regional Green Hydrogen Economy: WIVA P&G HyWest
Authors: Fleischhacker Nikolaus , Shakibi Nia Niusha , Coll Markus , Perwög Ewald , Schreiner Helmut , Burger Andreas , Stamatakis Emmanuel , Fleischhacker Ernst
Published: April 2023

The regional parliament of Tyrol in Austria adopted the climate, energy, and resources strategy “Tyrol 2050 energy autonomous” in 2014 with the aim to become climate neutral and energy autonomous. “Use of own resources before others do, or have to do” is the main principle within this long-term strategic approach, in which the “power on demand” process is a main building block and the “power-to-hydrogen” process covers the intrinsic lack of a long-term, large-scale storage of electricity. Within this long-term strategy, the national research and development (R&D) flagship project WIVA P&G HyWest (ongoing since 2018) aims at the establishment of the first sustainable, business-case-driven, regional, green hydrogen economy in central Europe. This project is mainly based on the logistic principle and is a result of synergies between three ongoing complementary implementation projects. Among these three projects, to date, the industrial research within “MPREIS Hydrogen” resulted in the first green hydrogen economy. One hydrogen truck is operational as of January 2023 in the region of Tyrol for food distribution and related monitoring studies have been initiated. To fulfil the logistic principle as the main outcome, another two complementary projects are currently being further implemented.
Application of an NDIR Sensor System Developed for Early Thermal Runaway Warning of Automotive Batteries
Authors: Han Yulu , Zhao Yongmin , Ming Anjie , Fang Yanyan , Fang Sheng , Bi Shansong , Chen Jiezhi , Xu Ran , Wei Feng , Mao Changhui
Published: April 2023

This paper proposes to apply a newly developed Non-Dispersive Infrared Spectroscopy (NDIR) gas sensing system composed of pyroelectric infrared detectors to monitor the thermal runaway (TR) process of lithium-ion batteries in real time and achieve an early warning system for the battery TR process. The new Electrical Vehicle Safety—Global Technical Regulation (EVS-GTR) requires that a warning be provided to passengers at least five minutes before a serious incident. The experimental results indicate that carbon dioxide and methane gas were detected during the overcharge test of the automotive battery, and the target gas was detected 25 s in advance before the battery TR when the battery vent was closed. In order to further explore the battery TR mechanism, an experiment was carried out using the battery sample with the battery vent opened. The target gas was detected about 580 s before the battery temperature reached the common alarm temperature (60 °C) of the battery management system (BMS). In this study, the beneficial effects of NDIR gas sensors in the field of thermal runaway warnings for automotive batteries were demonstrated and showed great application prospects and commercial value.
Experimental Study of the Effect of Humidity on Air Filter Material Performance
Authors: Zhang Tao , Fu Zhongguang , Zhou Hao
Published: April 2023

A large number of application cases show that air filter media are easy to fail under extreme conditions of high humidity, haze, rain and snow, thus seriously affecting the energy efficiency of gas turbines. To study the impact of humidity on the dust-holding performance of filter media, three typical filter media applied for gas turbines with a similar efficiency are selected, and their dust-holding performance is investigated at a humidity of 30%, 60% and 75%, respectively. The results showed that the dust-holding pressure drop curves of three filter media were divided into two phases. With the increase of humidity, the increasing pressure drop rate of three filter media decreased. The pressure drop synthetic fiber, glass fiber composite filter media and the synthetic fiber composite filter media with a sandwich structure were more significantly affected by humidity during the filter cake filtration phase. Under the same conditions, filter media with a sandwich structure had the highest dust-holding capacity, while the electrospun fiber composite filter material had the lowest one. The dustcake formed on the surface of the filter media that consist of a pure synthetic fiber or a small amount of plant fiber is significantly affected by humidity.
Quantitative Analysis of Surface Partial Discharges through Radio Frequency and Ultraviolet Signal Measurements
Authors: Kozioł Michał , Nagi Łukasz , Boczar Tomasz , Nadolny Zbigniew
Published: April 2023

In high voltage insulation systems, dielectric materials may be exposed to partial discharges (PD), which can lead to equipment failures and safety hazards. Therefore, it is crucial to detect and characterize PD activity on the surface of insulation systems. Techniques such as radio frequency signal analysis and ultraviolet radiation emission detection are commonly used for this purpose. In this research study, an analysis was conducted on the signals emitted by surface PD in the radio frequency and ultraviolet radiation emission ranges. The goal was to indicate possible directions for further basic research aimed at building a knowledge base and improving measurement methods. The analysis confirmed that radio frequency and ultraviolet signal analysis can provide important information about the activity and location of PD on the surface, including the intensity and nature of PD. The experimental investigation presented in this paper provides valuable insights into the potential for using radio frequency and ultraviolet signals to enhance diagnostic techniques for monitoring the condition of insulation systems in high-voltage equipment.