bluuebunny/crossref_metadata_2025 huggingface dataset:
EVM: An Educational Virtual Reality Modeling Tool; Evaluation Study with Freshman Engineering Students
Authors: Conesa-Pastor Julián , Contero Manuel
Published: January 2022

Educational Virtual Modeling (EVM) is a novel VR-based application for sketching and modeling in an immersive environment designed to introduce freshman engineering students to modeling concepts and reinforce their understanding of the spatial connection between an object and its 2D projections. It was built on the Unity 3D game engine and Microsoft’s Mixed Reality Toolkit (MRTK). EVM was designed to support the creation of the typical parts used in exercises in basic engineering graphics courses with a special emphasis on a fast learning curve and a simple way to provide exercises and tutorials to students. To analyze the feasibility of using EVM for this purpose, a user study was conducted with 23 freshmen and sophomore engineering students that used both EVM and Trimble SketchUp to model six parts using an axonometric view as the input. Students had no previous experience in any of the two systems. Each participant went through a brief training session and was allowed to use each tool freely for 20 min. At the end of the modeling exercises with each system, the participants rated its usability by answering the System Usability Scale (SUS) questionnaire. Additionally, they filled out a questionnaire for assessment of the system functionality. The results demonstrated a very high SUS score for EVM (M = 92.93, SD = 6.15), whereas Trimble SketchUp obtained only a mean score of 76.30 (SD = 6.69). The completion time for the modeling tasks with EVM showed its suitability for regular class use, despite the fact that it usually takes longer to complete the exercises in the system than in Trimble SketchUp. There were no statistically significant differences regarding functionality assessment. At the end of the experimental session, participants were asked to express their opinion about the systems and provide suggestions for the improvement of EVM. All participants showed a preference for EVM as a potential tool to perform exercises in the engineering graphics course.
Numerical Simulation and Experiment of a High-Efficiency Tunnel Oxide Passivated Contact (TOPCon) Solar Cell Using a Crystalline Nanostructured Silicon-Based Layer
Authors: Khokhar Muhammad Quddamah , Hussain Shahzada Qamar , Zahid Muhammad Aleem , Pham Duy Phong , Cho Eun-Chel , Yi Junsin
Published: January 2022

We report on the tunnel oxide passivated contact (TOPCon) using a crystalline nanostructured silicon-based layer via an experimental and numerical simulation study. The minority carrier lifetime and implied open-circuit voltage reveals an ameliorated passivation property, which gives the motivation to run a simulation. The passivating contact of an ultra-thin silicon oxide (1.2 nm) capped with a plasma enhanced chemical vapor deposition (PECVD) grown 30 nm thick nanocrystalline silicon oxide (nc-SiOx), provides outstanding passivation properties with low recombination current density (Jo) (~1.1 fA/cm2) at a 950 °C annealing temperature. The existence of a thin silicon oxide layer (SiO2) at the rear surface with superior quality (low pinhole density, Dph < 1 × 10−8 and low interface trap density, Dit ≈ 1 × 108 cm−2 eV−1), reduces the recombination of the carriers. The start of a small number of transports by pinholes improves the fill factor (FF) up to 83%, reduces the series resistance (Rs) up to 0.5 Ω cm2, and also improves the power conversion efficiency (PEC) by up to 27.4%. The TOPCon with a modified nc-SiOx exhibits a dominant open circuit voltage (Voc) of 761 mV with a supreme FF of 83%. Our simulation provides an excellent match with the experimental results and supports excellent passivation properties. Overall, our study proposed an ameliorated knowledge about tunnel oxide, doping in the nc-SiOx layer, and additionally about the surface recombination velocity (SRV) impact on TOPCon solar cells.
Vegetation Removal on 3D Point Cloud Reconstruction of Cut-Slopes Using U-Net
Authors: Wang Ying , Koo Ki-Young
Published: January 2022

The 3D point cloud reconstruction from photos taken by an unmanned aerial vehicle (UAV) is a promising tool for monitoring and managing risks of cut-slopes. However, surface changes on cut-slopes are likely to be hidden by seasonal vegetation variations on the cut-slopes. This paper proposes a vegetation removal method for 3D reconstructed point clouds using (1) a 2D image segmentation deep learning model and (2) projection matrices available from photogrammetry. For a given point cloud, each 3D point of it is reprojected into the image coordinates by the projection matrices to determine if it belongs to vegetation or not using the 2D image segmentation model. The 3D points belonging to vegetation in the 2D images are deleted from the point cloud. The effort to build a 2D image segmentation model was significantly reduced by using U-Net with the dataset prepared by the colour index method complemented by manual trimming. The proposed method was applied to a cut-slope in Doam Dam in South Korea, and showed that vegetation from the two point clouds of the cut-slope at winter and summer was removed successfully. The M3C2 distance between the two vegetation-removed point clouds showed a feasibility of the proposed method as a tool to reveal actual change of cut-slopes without the effect of vegetation.
Fuzzy Regulator for Two-Phase Gas–Liquid Pipe Flows Control
Authors: Fiderek Paweł , Kucharski Jacek , Wajman Radosław
Published: January 2022

The paper presents an intelligent module to control dynamic two-phase gas–liquid mixtures pipelines flow processes. The module is intelligent because it uses the algorithm based on AI methods, namely, fuzzy logic inference, to build the fuzzy regulator concept. The developed modification has allowed to design and implement the black-box type regulator. Therefore, it is not required to determine any of the complicated computer models of the flow rig, which is unfortunately necessary when using the classic regulators. The inputs of the regulator are four linguistic variables that are decomposed into two classes and two methods of fuzzification. The first input class describes the current values of gas and liquid pipe flows, which at the same time are the controlled values manipulated to generate desired flow type. The second class of the input signals contains a current flow state, namely, its name and the name preferred by the operator flow type. This approach improves the control accuracy since the given flow type can be generated with different gas and liquid volume fractions. Those values can be optimized by knowing the current flow type. Moreover, the fuzzification algorithm used for the input signals included in the first-class covers the current crisp signal value and its trend making the inference more accurate and resistant to slight measurement system inaccuracy. This approach of defined input signals in such environments is used for the first time. Considering all mentioned methods, it is possible to generate the desired flow type by manipulating the system input signals by minimum required values. Furthermore, a flow type can be changed by adjusting only one of the input signals. As an output of the inference process, two linguistic values are received, which are fuzzified adjustment values of the liquid pump and gas flow meter. The regulator looks to be universal, and it can be adopted by multiple test and production rigs. Moreover, once configured with a dedicated rig, it can be easily operated by the non (domain) technical staff. The usage of fuzzy terms makes understanding both the control strategy working principles and the obtained results easy.
A Supervised Neural Network Control for Magnetorheological Damper in an Aircraft Landing Gear
Authors: Luong Quoc-Viet , Jo Bang-Hyun , Hwang Jai-Hyuk , Jang Dae-Sung
Published: January 2022

This paper adopts an intelligent controller based on supervised neural network control for a magnetorheological (MR) damper in an aircraft landing gear. An MR damper is a device capable of adjusting the damping force by changing the magnetic field generated in electric coils. Applying an MR damper to the landing gears of an aircraft could minimize the impact at landing and increase the impact absorption efficiency. Various techniques proposed for controlling the MR damper in aircraft landing gears require information on the damper force or the mass of the aircraft to determine optimal parameters and control commands. This information is obtained by estimation with a model in a practical operating environment, and the accompanying inaccuracies cause performance degradation. Machine learning-based controllers have also been proposed to address model dependency but require a large number of drop test data. Unlike simulations, which can conduct a large number of virtual drop tests, the cost and time are limited in the actual experimental environment. Therefore, a neural network controller with supervised learning is proposed in this paper to simulate the behavior of a proven controller only with system states. The experimental data generated by applying the hybrid controller with the exact mass and force information, which has demonstrated high performance among the existing techniques, are set as the target for supervised learning. To verify the effectiveness of the proposed controller, drop test experiments using the intelligent controller and the hybrid controller with and without exact information about aircraft mass and force are executed. The experimental results from the drop tests of a landing gear show that the proposed controller maintains superior performance to the hybrid controller without using explicit damper models or any information on the aircraft mass or strut force.
Kalman Filter Implementation of Subglottal Impedance-Based Inverse Filtering to Estimate Glottal Airflow during Phonation
Authors: Cortés Juan P. , Alzamendi Gabriel A. , Weinstein Alejandro J. , Yuz Juan I. , Espinoza Víctor M. , Mehta Daryush D. , Hillman Robert E. , Zañartu Matías
Published: January 2022

Subglottal Impedance-Based Inverse Filtering (IBIF) allows for the continuous, non-invasive estimation of glottal airflow from a surface accelerometer placed over the anterior neck skin below the larynx. It has been shown to be advantageous for the ambulatory monitoring of vocal function, specifically in the use of high-order statistics to understand long-term vocal behavior. However, during long-term ambulatory recordings over several days, conditions may drift from the laboratory environment where the IBIF parameters were initially estimated due to sensor positioning, skin attachment, or temperature, among other factors. Observation uncertainties and model mismatch may result in significant deviations in the glottal airflow estimates; unfortunately, they are very difficult to quantify in ambulatory conditions due to a lack of a reference signal. To address this issue, we propose a Kalman filter implementation of the IBIF filter, which allows for both estimating the model uncertainty and adapting the airflow estimates to correct for signal deviations. One-way analysis of variance (ANOVA) results from laboratory experiments using the Rainbow Passage indicate an improvement using the modified Kalman filter on amplitude-based measures for phonotraumatic vocal hyperfunction (PVH) subjects compared to the standard IBIF; the latter showing a statistically difference (p-value =0.02, F=4.1) with respect to a reference glottal volume velocity signal estimated from a single notch filter used here as ground-truth in this work. In contrast, maximum flow declination rates from subjects with vocal phonotrauma exhibit a small but statistically difference between the ground-truth signal and the modified Kalman filter when using one-way ANOVA (p-value =0.04, F=3.3). Other measures did not have significant differences with either the modified Kalman filter or IBIF compared to ground-truth, with the exception of H1-H2, whose performance deteriorates for both methods. Overall, both methods (modified Kalman filter and IBIF) show similar glottal airflow measures, with the advantage of the modified Kalman filter to improve amplitude estimation. Moreover, Kalman filter deviations from the IBIF output airflow might suggest a better representation of some fine details in the ground-truth glottal airflow signal. Other applications may take more advantage from the adaptation offered by the modified Kalman filter implementation.
Behavioral Parameter Field for Human Abnormal Behavior Recognition in Low-Resolution Thermal Imaging Video
Authors: Wang Baodong , Jiang Xiaofeng , Dong Zihao , Li Jinping
Published: January 2022

In recent years, thermal imaging cameras are widely used in the field of intelligent surveillance because of their special imaging characteristics and better privacy protection properties. However, due to the low resolution and fixed location for current thermal imaging cameras, it is difficult to effectively identify human behavior using a single detection method based on skeletal keypoints. Therefore, a self-update learning method is proposed for fixed thermal imaging camera scenes, called the behavioral parameter field (BPF). This method can express the regularity of human behavior patterns concisely and directly. Firstly, the detection accuracy of small targets under low-resolution video is improved by optimizing the YOLOv4 network to obtain a human detection model under thermal imaging video. Secondly, the BPF model is designed to learn the human normal behavior features at each position. Finally, based on the learned BPF model, we propose to use metric modules, such as cosine similarity and intersection over union matching, to accomplish the classification of human abnormal behaviors. In the experimental stage, the living scene of the indoor elderly living alone is applied as our experimental case, and a variety of detection models are compared to the proposed method for verifying the effectiveness and practicability of the proposed behavioral parameter field in the self-collected thermal imaging dataset for the indoor elderly living alone.
End-to-End Deep Learning CT Image Reconstruction for Metal Artifact Reduction
Authors: Bauer Dominik F. , Ulrich Constantin , Russ Tom , Golla Alena-Kathrin , Schad Lothar R. , Zöllner Frank G.
Published: January 2022

Metal artifacts are common in CT-guided interventions due to the presence of metallic instruments. These artifacts often obscure clinically relevant structures, which can complicate the intervention. In this work, we present a deep learning CT reconstruction called iCTU-Net for the reduction of metal artifacts. The network emulates the filtering and back projection steps of the classical filtered back projection (FBP). A U-Net is used as post-processing to refine the back projected image. The reconstruction is trained end-to-end, i.e., the inputs of the iCTU-Net are sinograms and the outputs are reconstructed images. The network does not require a predefined back projection operator or the exact X-ray beam geometry. Supervised training is performed on simulated interventional data of the abdomen. For projection data exhibiting severe artifacts, the iCTU-Net achieved reconstructions with SSIM = 0.970±0.009 and PSNR = 40.7±1.6. The best reference method, an image based post-processing network, only achieved SSIM = 0.944±0.024 and PSNR = 39.8±1.9. Since the whole reconstruction process is learned, the network was able to fully utilize the raw data, which benefited from the removal of metal artifacts. The proposed method was the only studied method that could eliminate the metal streak artifacts.
Lensless Optical Encryption of Multilevel Digital Data Containers Using Spatially Incoherent Illumination
Authors: Cheremkhin Pavel , Evtikhiev Nikolay , Krasnov Vitaly , Ryabcev Ilya , Shifrina Anna , Starikov Rostislav
Published: January 2022

The necessity of the correction of errors emerging during the optical encryption process led to the extensive use of data containers such as QR codes. However, due to specifics of optical encryption, QR codes are not very well suited for the task, which results in low error correction capabilities in optical experiments mainly due to easily breakable QR code’s service elements and byte data structure. In this paper, we present optical implementation of information optical encryption system utilizing new multilevel customizable digital data containers with high data density. The results of optical experiments demonstrate efficient error correction capabilities of the new data container.
Large-Scale Truss Topology and Sizing Optimization by an Improved Genetic Algorithm with Multipoint Approximation
Authors: Dong Tianshan , Chen Shenyan , Huang Hai , Han Chao , Dai Ziqi , Yang Zihan
Published: January 2022

Truss size and topology optimization problems have recently been solved mainly by many different metaheuristic methods, and these methods usually require a large number of structural analyses due to their mechanism of population evolution. A branched multipoint approximation technique has been introduced to decrease the number of structural analyses by establishing approximate functions instead of the structural analyses in Genetic Algorithm (GA) when GA addresses continuous size variables and discrete topology variables. For large-scale trusses with a large number of design variables, an enormous change in topology variables in the GA causes a loss of approximation accuracy and then makes optimization convergence difficult. In this paper, a technique named the label–clip–splice method is proposed to improve the above hybrid method in regard to the above problem. It reduces the current search domain of GA gradually by clipping and splicing the labeled variables from chromosomes and optimizes the mixed-variables model efficiently with an approximation technique for large-scale trusses. Structural analysis of the proposed method is extremely reduced compared with these single metaheuristic methods. Numerical examples are presented to verify the efficacy and advantages of the proposed technique.
Failure Analysis of Steel Fiber-Reinforced Concrete T-Beams without Shear Stirrups
Authors: Rhee Inkyu
Published: January 2022

The shear failure of a reinforced concrete member is a sudden diagonal tension failure; flexible failure is gradual, associated with significant cracks, and leads to extensive sagging. Therefore, reinforced shear rebars are commonly used to ensure that flexible failure occurs before shear failure under extreme conditions. Extensive efforts are underway to replace conventional shear reinforcements with steel fibers. Here, a nonlinear analysis of a steel fiber-reinforced concrete T-beam was performed in order to estimate the maximum shear capacity with the aid of experimental test data. A continuum-damaged plasticity model and modified compression field theory were used for nonlinear analysis. Three 360 × 360-mm web elements were selected between the shear span; changes in the principal axis caused by crack development and propagation were traced. Changes in the crack angle according to the average strain of the bottom longitudinal reinforcement and the vertical strain of the web element were also determined. For verification, a strut-tie model was used to predict shear capacity. The experimental results and the finite element analyses were in good agreement.
Evaluation of Stereolithography-Based Additive Manufacturing Technology for BaTiO3 Ceramics at 465 nm
Authors: Chugunov Svyatoslav , Smirnov Andrey , Kholodkova Anastasia , Tikhonov Andrey , Dubinin Oleg , Shishkovsky Igor
Published: January 2022

A piezoceramic BaTiO3 material that is difficult for 3D printing was tested with a homemade laser-based stereolithography (SLA) setup. The high light absorbance of BaTiO3 in the spectral range of 350–410 nm makes this material hardly usable with most commercial SLA 3D printers. The typical polymerization depth of BaTiO3 ceramic pastes in this spectral range hardly reaches 30–50 µm for 40 vol % powder loading. A spectral change to 465 nm was realized in this work via a robot-based experimental SLA setup to improve the 3D printing efficiency. The ceramic paste was prepared from a preconditioned commercial BaTiO3 powder and used for 3D printing. The paste’s polymerization was investigated with variation of powder fraction (10–55 vol %), speed of a laser beam (1–10 mm/s, at constant laser power), and a hatching spacing (100–1000 µm). The polymerization depths of over 100 µm were routinely reached with the 465 nm SLA for pastes having 55 vol % powder loading. The spectral shift from 350–410 nm spectral region to 465 nm reduced the light absorption by BaTiO3 and remedied the photopolymerization process, emphasizing the importance of comprehensive optical analysis of prospective powders in SLA technology. Two multi-layered objects were 3D-printed to demonstrate the positive effect of the spectral shift.
A Method for Recognition of Sudden Commencements of Geomagnetic Storms Using Digital Differentiating Filters
Authors: Getmanov Victor , Sidorov Roman , Gvishiani Alexei
Published: January 2022

This article describes a method for recognizing sudden commencement events using digital differentiating filters. This method is applied to INTERMAGNET observatory data. Maximum amplitude derivatives for the magnetic components (X, Y, Z) and the total intensity (F) of the geomagnetic field are introduced, and the decision-making rule is formulated. The authors developed a procedure for selecting optimal digital differentiating filters. Estimates of probabilities of correct and false recognition of sudden commencements were obtained. The calculations of the probabilistic characteristics have confirmed the effectiveness of the method.
Practical, Low-Cost Fault Injection Attacks on Personal Smart Devices
Authors: Delarea Shaked , Oren Yossi
Published: January 2022

Fault attacks are traditionally considered under a threat model that assumes the device under test is in the possession of the attacker. We propose a variation on this model. In our model, the attacker integrates a fault injection circuit into a malicious field-replaceable unit, or FRU, which is later placed by the victim in close proximity to their own device. Examples of devices which incorporate FRUs include interface cards in routers, touch screens and sensor assemblies in mobile phones, ink cartridges in printers, batteries in health sensors, and so on. FRUs are often installed by after-market repair technicians without properly verifying their authenticity, and previous works have shown they can be used as vectors for various attacks on the privacy and integrity of smart devices. We design and implement a low-cost fault injection circuit suitable for placement inside a malicious FRU, and show how it can be used to practically extract secrets from a privileged system process through a combined hardware-software approach, even if the attacker software application only has user-level permissions. Our prototype produces highly effective and repeatable attacks, despite its cost being several orders of magnitude less than that of commonly used fault injection analysis lab setups. This threat model allows fault attacks to be carried out remotely, even if the device under test is in the hands of the victim. Considered together with recent advances in software-only fault attacks, we argue that resistance to fault attacks should be built into additional classes of devices.
Effectiveness of Auditory Distraction and Brief Relaxation Therapy in Reducing Anxiety in Dental Patients Undergoing Extraction: A Randomized Controlled Trial
Authors: Alhazmi Yaser Ali , Mobarki Amal Mohammed , Hakami Wala’a Haser , Akairi Hanin Naser , Altherwi Yusra Khalid , Quadri Mir Faeq Ali
Published: January 2022

Objective: This study compared the effectiveness of auditory distraction and brief relaxation therapy for reducing anxiety in patients undergoing tooth extraction. Methods: A non-blind, three-armed, randomized control trial was carried out. The targeted study population were patients who needed extraction of a non-restorable and non-mobile molar tooth. Eighty-six patients were recruited; the brief relaxation therapy and auditory distraction groups had 32 participants each, while 10 of the 22 participants in the control group were excluded due to missing data. The Hierarchical Anxiety Questionnaire was used to assess the anxiety level. The Mann–Whitney U or Kruskal–Wallis test was performed to compare means between the groups. The before and after comparisons in each group were carried out using the Wilcoxon Signed-Rank test. The alpha value was set at 0.05, and data were analyzed using SPSS version 24. Results: The mean anxiety score after brief relaxation therapy and auditory distraction had significantly decreased (p < 0.001). Although not significant (p = 0.13), there was a slight increase in the anxiety score of the study participants in the control group just before the extraction procedure. Brief relaxation therapy was significantly effective in reducing anxiety scores in comparison to the control group (MD = 5.87, 95% CI = 2.58, 9.17; p = 0.001), but auditory distraction was not (p = 0.14). Conclusion: Both auditory distraction and brief relaxation therapy were effective in reducing patient anxiety before a dental procedure. Furthermore, it would be interesting to learn if these findings remain consistent for more complex dental procedures, such as surgical removal of an impacted third molar.
An Internet of Things (IoT)-Based Master-Slave Regionalized Intelligent LED-Light-Controlling System
Authors: Lee Chun-Te , Chen Liang-Bi , Chu Huan-Mei , Hsieh Che-Jen , Liang Wei-Chieh
Published: January 2022

Reducing residential and industrial electricity consumption has been a goal of governments around the world. Lighting sources account for a large portion of the whole energy/power consumption. Unfortunately, most of the existing installed lighting systems are ancient and have poor energy efficiency. Today, many manufacturers have introduced light-controlling systems into the current market. However, existing light controlling systems may not be successfully applied to buildings, streets, and industrial buildings due to high costs and difficult installation and maintenance. To combat this issue, this article presents an easy-to-install, low-cost, Master-Slave intelligent LED light-controlling system based on Internet of Things (IoT) techniques. The benefit of using the proposed system is that the brightness of the LED lights in the same zone can be changed simultaneously to save in energy consumption. Furthermore, the parameters of the LED lights can be directly set. Moreover, the related data are collected and uploaded to a cloud platform. In this article, we use 15 W T8 LED tubes (non-induction lamps) as a case study. When the proposed system is installed in a zone with few people, the energy-saving rate is as high as 90%. Furthermore, when 12 people pass by a zone within one hour, its energy-saving rate can reach 81%. Therefore, the advantages of using the proposed system include: (1) the original lamp holder can be retained; (2) no wiring is required; and (3) no server is set up. Moreover, the goal of energy saving can also be achieved. As a result, the proposed system changes the full-dark mode of the available sensor lamp to the low power low-light mode for standby. Further, it makes the sensor lamps in the same zone brighten or low-light way simultaneously, which can quickly complete large-scale energy-saving and convenient control functions of intelligent LED lighting controlling system.
Polymorphism of 16s rRNA Gene: Any Effect on the Biomolecular Quantitation of the Honey Bee (Apis mellifera L., 1758) Pathogen Nosema ceranae?
Authors: Cilia Giovanni , Luchetti Giacomo , Nanetti Antonio
Published: January 2022

The microsporidian Nosema ceranae is a severe threat to the western honey bee Apis mellifera, as it is responsible for nosemosis type C, which leads the colonies to dwindle and collapse. Infection quantification is essential to clinical and research aims. Assessment is made often with molecular assays based on rRNA genes, which are present in the N. ceranae genome as multiple and polymorphic copies. This study aims to compare two different methods of Real-Time PCR (qPCR), respectively relying on the 16S rRNA and Hsp70 genes, the first of which is described as a multiple and polymorphic gene. Young worker bees, hatched in the laboratory and artificially inoculated with N. ceranae spores, were incubated at 33 °C and subject to different treatment regimens. Samples were taken post-infection and analyzed with both qPCR methods. Compared to Hsp70, the 16S rRNA method systematically detected higher abundance. Straightforward conversion between the two methods is made impossible by erratic 16s rRNA/Hsp70 ratios. The 16s rRNA polymorphism showed an increase around the inoculated dose, where a higher prevalence of ungerminated spores was expected due to the treatment effects. The possible genetic background of that irregular distribution is discussed in detail. The polymorphic nature of 16S rRNA showed to be a limit in the infection quantification. More reliably, the N. ceranae abundance can be assessed in honey bee samples with methods based on the single-copy gene Hsp70.
Assessment of Building Automation and Control Systems in Danish Healthcare Facilities in the COVID-19 Era
Authors: Pedersen Jeanette Maria , Jebaei Farah , Jradi Muhyiddine
Published: January 2022

A well-designed and properly operated building automation and control system (BACS) is key to attaining energy-efficient operation and optimal indoor conditions. In this study, three healthcare facilities of a different type, age, and use are considered as case studies to investigate the functionalities of BACS in providing optimal air quality and thermal comfort. IBACSA, the first-of-its-kind instrument for BACS assessment and smartness evaluation, is used to evaluate the current systems and their control functionalities. The BACS assessment is reported and analyzed. Then, three packages of improvements were implemented in the three cases, focusing on (1) technical systems enhancement, (2) indoor air quality and comfort, and (3) energy efficiency. It was found that the ventilation system domain is the best performer in the three considered cases with an overall score of 52%, 89% and 91% in Case A, B, and C, respectively. On the other hand, domestic hot water domain scores are relatively low, indicating that this is an area where Danish healthcare facilities need to provide more concentration on. A key finding indicated by the assessment performed is that the three buildings score relatively very low when it comes to the impact criteria of energy flexibility and storage.
Short-Term Effect of Wearing of Extended Depth-of-Focus Contact Lenses in Myopic Children: A Pilot Study
Authors: Corpus Gema , Piñero David P.
Published: January 2022

This pseudo-experimental, prospective, and longitudinal pilot study was conducted to characterize the optical and visual changes occurring in the short-term wear of a hydrophilic contact lens (CL) based on extended focus technology (EDOF). A total of 30 eyes of 15 children (age, 6–16 years) were fitted with the EDOF CL Mylo (Mark’ennovy Care SL), performing an exhaustive follow-up for one month evaluating changes in visual acuity (VA), accommodation, binocularity, ocular aberrometry, visual quality, pupillometry, keratometry and biometry. Far and near VA with the CL improved progressively (p < 0.001), obtaining mean final binocular values of −0.08 ± 0.01 and −0.07 ± 0.01 LogMAR, respectively. There was a mean reduction in the accommodative LAG of 0.30 D (p < 0.001), without associated alterations in the magnitude of the phoria and fusional vergences (p ≥ 0.066). A controlled but statistically significant increase (p ≤ 0.005) of ocular high order aberration (HOA) root mean square (RMS), primary coma RMS, primary spherical aberration Zernike term and secondary astigmatism RMS was found with the CL wear. In conclusion, the EDOF CL evaluated provides adequate visual acuity and quality, with associated increased of several HOAs and a trend to reduction in the accommodative LAG that should be confirmed in future studies.
A New System of Sustainable Silico-Aluminous and Silicate Materials for Cultivation Purpose within Sustainable Buildings: Chemical-Physical, Antibacterial and Cytotoxicity Properties
Authors: Catauro Michelina , Dal Poggetto Giovanni , Pacifico Severina , Andreola Fernanda , Lancellotti Isabella , Barbieri Luisa
Published: January 2022

In this study, we compared the chemical-physical, antibacterial, and cytotoxicity properties of silico-aluminous and silicate materials for outdoor (green roof, planted walls) and indoor (urban farms, indoor microgreen gardens) cultivation purpose in a context of sustainable construction. Glasses and lightweight aggregates were tailored starting from waste, by-product, and post-consumer and bioproducts (packaging glass cullet, cattle bone flour ash, vegetable biomass ash, spent coffee ground, degreased from biomass of prepupae of Black Soldier Flies) mixed together with a national ferruginous red clay, quarry scrap pumice and, if necessary, with K2CO3 of reagent grade. The first type of material was obtained by melting at 1200 °C and the second one by powder sintering at 1000 °C. All specimens, subjected to antibacterial test, showed both low zone of inhibitions towards two Gram-negative and two Gram-positive bacterial strains. A cytotoxicity test on mouse embryonic fibroblast NIH-3T3 cell line directly exposed to the investigated materials was performed at three different exposure times (1 h, 3 h, and 6 h). Data acquired highlighted that the materials positively affected redox mitochondrial activity of the fibroblast cells. The concentrations of leachate heavy metals detected on selected materials in water at room temperature after 24 h were lower than the European law limit and an interesting release of P, K, and N nutrients was noted for those formulations designed for agronomic purposes. pH, falling on average within the 6.5–7.5 range, is optimal for most crops, and the specific conductivity <2 dS/m indicates no depression danger for crops. Both bulk density <1200 kg/m3 and porosity over 50% seem to ensure good performance of lightening, drainage, water reservation, and oxygenation of the roots.
Evaluation of Real-Time Kinematic Positioning and Deformation Monitoring Using Xiaomi Mi 8 Smartphone
Authors: Zeng Shulin , Kuang Cuilin , Yu Wenkun
Published: January 2022

Modern low-cost electronic devices can achieve high precision for global navigation satellite systems (GNSSs) and related applications. Recently, the pseudo-range and carrier phase have been directly obtained from a smartphone to establish a professional-level surveying device. Although promising results have been obtained by linking to an external GNSS antenna, the real-time kinematic (RTK) positioning performance requires further improvement when using the embedded smartphone antenna. We first investigate the observation quality characteristics of the Xiaomi Mi 8 smartphone. The carrier-to-noise-density ratio of L5/E5a signals is below that of L1/E1 signals, and the cycle slip and loss of lock are severe, especially for L5/E5a signals. Therefore, we use an improved stochastic model and ambiguity-resolution strategies to improve the short-baseline RTK positioning accuracy. Experimental results show that the ambiguity fixing rate can reach approximately 90% in 3 h of observations when using the embedded antenna, while the GPS/Galileo/BDS single-frequency combination is more suitable for smartphones. On the other hand, convergence takes 10–30 min, and the RTK positioning accuracy can reach 1 and 2 cm along the horizontal and vertical directions, respectively, if ambiguity is resolved correctly. Moreover, we verify the feasibility of using a mass-produced smartphone for deformation monitoring. Results from a simulated dynamic deformation experiment indicate that a smartphone can recognise deformations as small as 2 cm.
The Microfabricated Alkali Vapor Cell with High Hermeticity for Chip-Scale Atomic Clock
Authors: Jia Shuo , Jiang Zhiyuan , Jiao Binbin , Liu Xiaochi , Pan Yijie , Song Zhenfei , Qu Jifeng
Published: January 2022

Herein, a microfabricated millimeter-level vapor alkali cell with a high hermeticity is fabricated through a wet etching and single-chip anodic bonding process. The vapor cell, containing Rb and N2, was investigated in a coherent population trapping (CPT) setup for the application of a chip-scale atomic clock (CSAC). The contrast of CPT resonance is up to 1.1% within the only 1 mm length of light interacting with atom. The effects of some critical external parameters on the CPT resonance, such as laser intensity, cell temperature, and buffer gas pressure, are thoroughly studied and optimized. The improved microfabricated vapor cell also exhibited great potential for other chip-scale atomic devices.
Organizational Culture: The Key to Improving Service Management in Industry 4.0
Authors: Liu Shuo-Fang , Fan Yao-Jen , Luh Ding-Bang , Teng Pei-Shan
Published: January 2022

Industry 4.0 can enhance the operational efficiency of the supply chain, but the current research mainly focuses on analytics and smart things. Many companies integrate their organizations more closely with data by adopting Industry 4.0, but this study found that some companies have changed their leadership, organizational, and customer relationships through the adoption of CPS. Industry 4.0 is a socio-technical system that should be explored in terms of management practices, employee feedback, and the cause-and-effect relationship between them. This study proposes a modeling framework using the Su-field analysis of TRIZ method (Theory of Inventive Problem Solving) and applies the Partial Least Squares Structural Equation Modeling (PLS-SEM) method to investigate the relationship between leadership, organizational culture, and service management in the Taiwan industry. The results show that the data analysis, CPS, IoT, and intelligent technologies of Industry 4.0 can facilitate connections within the value chain and increase agility in response to environmental changes. Companies must have a good organizational culture and provide the right incentives to gain the organizational commitment of their employees to implement Industry 4.0.
Brown-Field Migration Aware Routing and Spectrum Assignment in Backbone Optical Networks
Authors: Yu Xiaosong , Wang Jiye , Zhang Kaixin , Lv Jiaqi , Zhao Yongli , Gao Kaiqiang , Guo Xuerang , Zhang Jie
Published: January 2022

With the development of optical networks technology, broad attention has been paid to flexible grid technology in optical networks due to its ability to carry large-capacity information as well as provide flexible and fine-grained services through on-demand spectrum resource allocation. However, a one-time green-field deployment of a flexible grid network may not be practical. The transition technology called the fixed/flex-grid optical networks is more applicable and highly pragmatic. In such network, many nodes would likely be upgraded from a fixed-grid to flex-grid. In fact, dynamic service provisioning during the process of a node upgrade in fixed/flex-grid optical networks have become a challenge because the service connection can be easily interrupted, which leads to considerable data loss because of node upgrade. To overcome this challenge, we propose a brown-field migration aware routing and spectrum assignment (BMA-RSA) algorithm in fixed/flex-grid optical networks. The aim is to construct a probabilistic migration label (PML) model. The well-designed label setting of PML can balance the relationship between distance and node-upgrade probability. Dynamic service provisioning operations are undertaken based on the PML model to achieve a migration-aware dynamic connection before network migration occurs. We also evaluate the performance of different service provisioning strategies under different traffic models. The simulation results show that the BMA-RSA algorithm can achieve: (1) the tradeoff between distance and node upgrade probability during the process of service provisioning; (2) lower service interruption compared with the traditional non-migration aware K-shortest-path routing and spectrum assignment algorithm.
Rotation Invariant Parallel Signal Processing Using a Diffractive Phase Element for Image Compression
Authors: Hamam Habib
Published: January 2022

We propose a new rotation invariant correlator using dimensionality reduction. A diffractive phase element is used to focus image data into a line which serves as input for a conventional correlator. The diffractive element sums information over each radius of the scene image and projects the result onto one point of a line located at a certain distance behind the image. The method is flexible, to a large extent, and might include parallel pattern recognition and classification as well as further geometrical invariance. Although the new technique is inspired from circular harmonic decomposition, it does not suffer from energy loss. A theoretical analysis, as well as examples, are given.
Application of Microgel as a Sorbent for Bisphenol Analysis in Liquid Food Samples
Authors: Kubiak Anna , Maćkiewicz Marcin , Karbarz Marcin , Biesaga Magdalena
Published: January 2022

Bisphenols are well-known endocrine disruptors that can easily migrate from plastic and can containers to food. Due to the complicated matrix and ultra-low concentrations of bisphenols in food, samples require extensive preparation before instrumental analysis. In this paper, an environmental sensitive microgel was employed as a sorbent for the preconcentration of four bisphenols, bisphenol A (BPA), bisphenol B (BPB), bisphenol E (BPE) and bisphenol F (BPF), from liquid food samples. Liquid chromatography with fluorescence detection (LC-FLD) was used for the quantification of bisphenols. By applying microgel solid-phase extraction procedure, the limits of detections achieved in liquid food samples can be lowered to 0.9 µg·L−1 for BPF and BPA, 2.3 µg·L−1 for BPE and 2.9 µg·L−1 for BPB. Only 5 mg of microgel was sufficient to achieve good recoveries (70.5–109%) with precision (RSD 0.21–5.01%, n = 3) for different analyzed liquid food samples spiked at concentration levels of 50 µg·L−1. In five out of twelve of the analyzed samples (pineapple, mandarin, peach, mushroom and pickles), they were contaminated with BPA, and the determined concentration was in the range of 6.2–22 µg·L−1; however, these results are below the specific migration limit (SML) set for BPA (50 µg·kg−1).
Effect of the Extended Rigid Flapping Trailing Edge Fringe on an S833 Airfoil
Authors: Yu Hongtao , Yang Zifeng
Published: January 2022

A 2D numerical simulation was conducted to investigate the effect of an extended rigid trailing edge fringe with a flapping motion on the S833 airfoil and its wake flow field, as an analogy of an owl’s wing. This study aims to characterize the influence of the extended flapping fringe on the aerodynamic performance and the wake flow characteristics downstream of the airfoil. The length (Le) and flapping frequencies (fe) of the fringe are the key parameters that dominate the impact on the airfoil and the flow field, given that the oscillation angular amplitude is fixed at 5°. The simulation results demonstrated that the airfoil with an extended fringe of 10% of the chord at a flapping frequency of fe = 110 Hz showed a substantial effect on the pressure distribution on the airfoil and the flow characteristics downstream of the airfoil. An irregular vortex street was predicted downstream, thus causing attenuations of the vorticities, and shorter streamwise gaps between each pair of vortices. The extended flapping fringe at a lower frequency than the natural shedding vortex frequency can effectively break the large vortex structure up into smaller scales, thus leading to an accelerated attenuation of vorticities in the wake.
Describing a Set of Points with Elliptical Areas: Mathematical Description and Verification on Operational Tests of Technical Devices
Authors: Wieczorek Bartosz , Kukla Mateusz , Warguła Łukasz
Published: January 2022

The purpose of this article was to present an algorithm for creating an ellipse for any data set represented on a two-dimensional reference frame. The study objective was to verify the developed method on real results of experimental tests with different subject matter. This article contains a mathematical algorithm to describe a set of points with elliptical areas. In addition, four results of tests with different subject matter are cited, based on which the developed method was verified. The verification of the method included checking the deviation of the geometric dimensions of the ellipse, the number of points contained within the ellipse, and the area of the ellipse. The implemented research methodology allowed to demonstrate the possibility of using the method of describing a set of points with elliptical areas, in order to determine quantitative parameters evaluating the results of the test. The presented results show the method’s applicability for the results obtained in four different operational tests: measurement of the human body’s gravity center position for a person propelling a wheelchair, measurement of marker position using motion capture methods, measurement of particulate emissions when using equipment powered by an internal combustion engine, and measurement of the muscle activity of the upper limb when propelling a hybrid manual-electric wheelchair. The performed experiments demonstrated that the method allows to describe about 85% of all measurement points with an ellipse.
Embedded Generative Air Pollution Model with Variational Autoencoder and Environmental Factor Effect in Ulaanbaatar City
Authors: Baldorj Bulgansaikhan , Tsagaan Munkherdene , Sereeter Lodoysamba , Bulkhbai Amanjol
Published: January 2022

Air pollution is one of the most pressing modern-day issues in cities around the world. However, most cities have adopted air quality measurement devices that only measure the past pollution levels without paying attention to the influencing factors. To obtain preliminary pollution information with regard to environmental factors, we developed a variational autoencoder and feedforward neural network-based embedded generative model to examine the relationship between air quality and the effects of environmental factors. In the model, actual SO2, NO2, PM2.5, PM10, and CO measurements from 2016 to 2020 were used, which were assembled from 15 differently located ground monitoring stations in Ulaanbaatar city. A wide range of weather and fuel measurements were used as the data for the influencing factors, and were collected over the same period as the air pollution data were recorded. The prediction results concerned all measurement stations, and the results were visualized as a spatial–temporal distribution of pollution and the performance of individual stations. A cross-validated R2 was used to estimate the entire pollution distribution through the regions as SO2: 0.81, PM2.5: 0.76, PM10: 0.89, and CO: 0.83. Pearson’s chi-squared tests were used for assessing each measurement station, and the contingency tables represent a high correlation between the actual and model results. The model can be applied to perform specific analysis of the interdependencies between pollution and environmental factors, and the performance of the model improves with long-range data.