bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparation of Antibacterial Nanosilver Solution Microcapsules and Their Impact on the Performance of Andoung Wood Surface Coating
Authors: Pan Pan , Yan Xiaoxing
Published: March 2023

In this paper, nanosilver solution was used as an antibacterial agent to prepare antibacterial microcapsules. The mass ratio of the core material to the wall material (Wcore: Wwall), the emulsifier’s hydrophilic–lipophilic balance (HLB) value, the mass ratio of ethanol to the emulsifier in solvent (Wcore: Wemulsion), and the rotational speed (r/min) were used to develop the four-factor, three-level orthogonal experiment, which was meant to investigate the most significant factors and the optimum process preparation parameters impacting the coating rate and yield of microcapsules. It was used to make an antibacterial coating that was applied to the surface paint film of a glass substrate and andoung wood, and it was mixed to the water-based primer with a content of 4%. Analyses of the mechanical, optical, and bactericidal characteristics were conducted. The micromorphology of the nanosilver solution microcapsules is influenced by the emulsifier’s HLB value. The color difference of the antibacterial coating film decreased with increasing emulsifier HLB value; however, the coating film’s gloss remained largely suitable. Additionally, the coating film’s transparency and tensile strength both decreased. It had minimal impact on the paint film’s surface hardness, but the adhesion and tensile strength showed a noticeable downward trend. The surface of the paint film was rough. Escherichia coli and Staphylococcus aureus were resistant to the antibacterial characteristics of the water-based primer film when it was combined with antibacterial nanosilver solution microcapsules by 80.7% and 74.55%, respectively. The coating film’s antibacterial properties were applied to the surface of the andoung wood, which were 75.7% and 71.0%, respectively, and somewhat decreased. In order to successfully inhibit bacteria, the nanosilver solution microcapsules were added to waterborne coatings. This ensures both the outstanding performance of the coating film and the effectiveness of the antibacterial effect. It expands the application prospects of antibacterial microcapsules in coatings.
Test Rig for the In Situ Measurement of the Elastic Tooth Deflection of Plastic Gears
Authors: Herzog Christoph , Drummer Dietmar
Published: March 2023

A new steel–plastic gear set testing methodology has been developed at the Institute of Polymer Technology (LKT). The in situ gear test rig analyses the timing differences between the index pulses of rotary encoders on the input and output shaft. This measurement principle enables the continuous measurement of the elastic tooth deflection on the one hand and permanent deformations and wear on the other hand by switching between a high loading torque and a low measuring torque. However, the elastic tooth deflection measurement using this principle has not yet been validated. Therefore, in situ gear tests using polybutylene terephthalate (PBT) gears were performed to evaluate the elastic tooth deflection of the plastic gear during operation. The results were compared to the results of pulsator tests. The comparison shows a very good correlation between the results of the newly developed in situ gear test rig and the well-established pulsator test rig. However, it has been shown that the test rig design creates a measuring offset due to angular displacements of the shafts due to torsion of test rig components.
Effect of Citric Acid on Swelling Resistance and Physicochemical Properties of Post-Crosslinked Electrospun Polyvinyl Alcohol Fibrous Membrane
Authors: Huang Ssu-Meng , Liu Shih-Ming , Tseng Hua-Yi , Chen Wen-Cheng
Published: March 2023

A series of electrospun polyvinyl alcohol (PVA) fiber membranes were crosslinked with citric acid (CA) at concentrations of 10, 20, and 30 wt.% (designated as CA10, CA20, and CA30). The effects of CA on the chemical structure, mechanical strength, swelling resistance, and cytotoxicity of the crosslinked PVA fibrous membranes were investigated. Infrared spectroscopy indicated the enhanced esterification of carboxyl and hydroxyl groups between CA and PVA. The modulus and strength of the electrospun PVA membrane increased due to the crosslinking between CA and PVA. The crosslinking of the PVA fiber matrix with CA increased the PVA binding point, thereby increasing the swelling resistance and modulus; however, the concentration of CA used was limited. Results showed that the water absorption of the PVA membranes decreased from 6.58 ± 0.04 g/g for CA10 to 3.56 ± 3.33 g/g for CA20 and 2.85 ± 0.40 g/g for CA30 with increasing CA. The water absorption remained unchanged after the membrane was soaked for a period of time, so no significant difference was found in the water absorption capacity of the same group after immersion from 1 h to 3 d. The tensile strength increased from 20.52 MPa of CA10 to 22.09 MPa of CA20. With an increased amount of CA used for crosslinking, the tensile strength and modulus of CA30 decreased to 11.48 and 13.94 MPa, respectively. Our study also showed that CA was not toxic to L929 cell viability when used for fiber crosslinking at less than 20 wt.% PVA, meaning it may be a good candidate as a support layer for guided tissue engineering.
Single-Micelle-Templated Synthesis of Hollow Barium Carbonate Nanoparticle for Drug Delivery
Authors: Bastakoti Bishnu Prasad , Bhattarai Nischal , Ashie Moses D. , Tettey Felix , Yusa Shin-ichi , Nakashima Kenichi
Published: March 2023

A laboratory-synthesized triblock copolymer poly(ethylene oxide-b-acrylic acid-b-styrene) (PEG-PAA-PS) was used as a template to synthesize hollow BaCO3 nanoparticles (BC-NPs). The triblock copolymer was synthesized using reversible addition–fragmentation chain transfer radical polymerization. The triblock copolymer has a molecular weight of 1.88 × 104 g/mol. Transmission electron microscopy measurements confirm the formation of spherical micelles with a PEG corona, PAA shell, and PS core in an aqueous solution. Furthermore, the dynamic light scattering experiment revealed the electrostatic interaction of Ba2+ ions with an anionic poly(acrylic acid) block of the micelles. The controlled precipitation of BaCO3 around spherical polymeric micelles followed by calcination allows for the synthesis of hollow BC-NPs with cavity diameters of 15 nm and a shell thickness of 5 nm. The encapsulation and release of methotrexate from hollow BC-NPs at pH 7.4 was studied. The cell viability experiments indicate the possibility of BC-NPs maintaining biocompatibility for a prolonged time.
Liquid Foam-Ethyl Vinyl Acetate Adhesive Systems for Lining Process of Paintings: Prospects of a User-Friendly, Harmless Alternative to Conventional Products
Authors: Tarantola Gaia , Medri Elena , Splendore Arianna , Lo Russo Francesca , Matteucci Chiara , Minelli Matteo
Published: March 2023

The lining of paintings is a process of conservation science and art restoration used to strengthen, flatten, or consolidate paintings on canvas by attaching by means of adhesives a second canvas to the back of the existing one. To this aim, the prospects of the use of ethyl vinyl acetate (EVA) resins in aqueous dispersion applied as an adhesive in a foam form have been investigated in the present study. The key physical properties of the foam have been investigated, with a deep focus on rheological behavior and the drying rate, comparing the results with those obtained using the liquid products that are commercially available. Dedicated mock-ups have been prepared to test the adhesive for the lining process, inspecting adhesion strength, colorimetric properties, and the influence on the possible chromatic and visual alteration of the surface, also looking at the chemical interaction with painting materials and the deterioration after an artificial ageing process. The results obtained clearly indicated that the proposed technology is very suitable for the targeted application, and an EVA water-based foamed dispersion can be used for paintings’ lining, in view of the ease of application, being an appropriate adhesion, no chemical interaction, nor the deterioration of the painting.
Multi-Block Copolymer Membranes Consisting of Sulfonated Poly(p-phenylene) and Naphthalene Containing Poly(arylene Ether Ketone) for Proton Exchange Membrane Water Electrolysis
Authors: Ko Eui Jin , Lee Eunju , Lee Jang Yong , Yu Duk Man , Yoon Sang Jun , Oh Keun-Hwan , Hong Young Taik , So Soonyong
Published: March 2023

Glassy hydrocarbon-based membranes are being researched as a replacement for perfluorosulfonic acid (PFSA) membranes in proton exchange membrane water electrolysis (PEMWE). Here, naphthalene containing Poly(arylene Ether Ketone) was introduced into the Poly(p-phenylene)-based multi-block copolymers through Ni(0)-catalyzed coupling reaction to enhance π-π interactions of the naphthalene units. It is discovered that there is an optimum input ratio of the hydrophilic monomer and NBP oligomer for the multi-block copolymers with high ion exchange capacity (IEC) and polymerization yield. With the optimum input ratio, the naphthalene containing copolymer exhibits good hydrogen gas barrier property, chemical stability, and mechanical toughness, even with its high IEC value over 2.4 meq g−1. The membrane shows 3.6 times higher proton selectivity to hydrogen gas than Nafion 212. The PEMWE single cells using the membrane performed better (5.5 A cm−2) than Nafion 212 (4.75 A cm−2) at 1.9 V and 80 °C. These findings suggest that naphthalene containing copolymer membranes are a promising replacement for PFSA membranes in PEMWE.
Insight into the Molecular Weight of Hydrophobic Starch Laurate-Based Adhesives for Paper
Authors: Watcharakitti Jidapa , Nimnuan Jaturavit , Krusong Kuakarun , Nanan Suwat , Smith Siwaporn Meejoo
Published: March 2023

Instead of using finite petroleum-based resources and harmful additives, starch can be used as a biodegradable, low-cost, and non-toxic ingredient for green adhesives. This work employs K3PO4 catalyzed transesterifications of cassava starch and methyl laurate at varying reaction times (1–10 h), resulting in the enhanced hydrophobicity of starch laurates. At longer reaction times, starch laurates having higher degrees of substitution (DS) were obtained. While starch laurates are the major products of transesterification, relatively low-molecular-weight byproducts (1%) were detected and could be hydrolyzed starches based on gel permeation chromatography results. Contact angle measurements confirmed the relatively high hydrophobicity of the modified starches compared with that of native starch. The modified starches were then employed to prepare water-based adhesives on paper (without any additional additives). Notably, the shear strength of the esterified starch adhesives appears to be independent of the DS of esterified samples, hence the transesterification reaction times. Additionally, the shear strength of water-based adhesives (0.67–0.73 MPa) for bonding to paper substrates is superior to that of two other commercially available glues by a factor of 10 to 80 percent.
Effect of Molecular Weight on the Dissolution Profiles of PEG Solid Dispersions Containing Ketoprofen
Authors: Le Khanh Ha Pham , Haimhoffer Ádám , Nemes Dániel , Józsa Liza , Vasvári Gábor , Budai István , Bényei Attila , Ujhelyi Zoltán , Fehér Pálma , Bácskay Ildikó
Published: March 2023

Solid dispersions are typically binary systems with a hydrophilic matrix polymer and a lipophilic active substance. During formulation, the drug undergoes a crystalline to amorphous phase transition, which leads to a supersaturated solution providing enhanced bioavailability. The interaction of the active substance and the polymer is unique and influences the level of supersaturation. We aimed to investigate the relationship between low molecular weight polyethylene glycol derivates PEG 1000, 1500, and 2000 and ketoprofen regarding the effect of molecular weight. The physicochemical properties of solid dispersions prepared with hot melt homogenization and their respective physical mixtures were investigated with Fourier transform infrared spectroscopy, powder X-ray diffraction and scanning electron microscopy techniques. A phase solubility study was carried out in hydrochloric acid media which showed no difference between the three polymers, but the dissolution curves differed considerably. PEG 1000 had higher percentage of released drug than PEG 1500 and 2000, which had similar results. These results indicate that when multiple low molecular weight PEGs are suitable as matrix polymers of solid dispersions, the molecular weight has only limited impact on physicochemical characteristics and interactions and further investigation is needed to select the most applicable candidate.
Institutio Sui Generis: Searching for a Global Catholic University during the 1970s
Authors: Lemke Duque Carl Antonius
Published: March 2023

This study provides a critical look at the Catholic search for a global university of the future during the 1970s. It focuses on proposals and arguments from the Canadian theologian and sociologist Hervé Carrier SJ (1921–2014), who was rector of the Pontificia Università Gregoriana between 1966 and 1978. To understand his idea of the university, three aspects are key: firstly, French and German sociologists’ postwar dialogue on modern secularization; secondly, Karl Jaspers’ (1883–1969) concept of the unconditional search for truth; and thirdly, the lifelong education paradigm as a tool for regaining a supposed authenticity of the individual, conceived as a prerequisite for society and politics. Analyzing these keys brings out a critical evaluation of the limits associated with the subjectivity consciousness development at Catholic higher education institutions.
A Non-Uniform Interrupted-Sampling Repeater Jamming Method for Intra-Pulse Frequency Agile Radar
Authors: Sun Zongzheng , Quan Yinghui , Liu Zhixing
Published: March 2023

The existing research proposes an intra-pulse frequency agile radar waveform with “active” anti-jamming characteristics. It uses the discontinuity and periodicity of the interrupted-sampling repeater jamming and combines the anti-jamming algorithm to effectively suppress interrupted-sampling repeater jamming. In order to improve the jamming effectiveness of the interferer for the intra-pulse frequency agile waveform, this paper proposes to jam the intra-pulse frequency agile radar by using a non-uniform interrupted-sampling and forwarding method under parameter constraints. The proposed method first obtains the sub-pulse width of the intra-pulse frequency agile radar waveform by parameter estimation of the intercepted intra-pulse frequency agile radar signal through time–frequency ridge extraction and wavelet transform. Then, we construct non-uniform interrupted-sampling repeater jamming based on sub-pulse width constraint interference parameters. Theoretical analysis and results show that the non-uniform interrupted-sampling forwarding under parameter constraints makes it challenging to suppress interference in multiple domains, such as the time–frequency and pulse compression domain for intra-pulse frequency agile radar, which significantly improves the jamming capability of the jammer for intra-pulse frequency agile radar.
Proof and Application of Discriminating Ocean Oil Spills and Seawater Based on Polarization Ratio Using Quad-Polarization Synthetic Aperture Radar
Authors: Xie Tao , Ouyang Ruihang , Perrie Will , Zhao Li , Zhang Xiaoyun
Published: March 2023

This paper focuses on the proof and application of discriminating between oil spills and seawater (including the “look-alikes”, named low wind areas) based on the polarization ratio. A new relative polarization ratio (PRr) method is proposed, which is based on the difference between the scattering mechanism and the dielectric constant for oil spills compared to that of seawater. The case study found that (1) PRr numerically amplifies the contrast between oil spills and seawater, reduces the difference between low wind areas and ordinary seawater, and exhibits better details of the image; (2) the threshold method based on Euclidean distance can obtain the highest classification overall accuracy within the allowable error range, and can be widely used in the study of different incidence angles and environmental conditions; and (3) the identification of oil spills and seawater by the proposed methods can largely avoid the misjudgment of low wind areas as oil spills. Considering visual interpretation as the reference ‘ground truth’, the overall classification accuracy of all cases is more than 95%; only the edge of the diffuse thin oil slick and oil–water mixture is difficult to identify. This method can serve as an effective supplement to existing oil spill detection methods.
Ground-Based Oblique-View Photogrammetry and Sentinel-1 Spaceborne RADAR Reflectivity Snow Melt Processes Assessment on an Arctic Glacier
Authors: Friedt Jean-Michel , Bernard Éric , Griselin Madeleine
Published: March 2023

The snowpack evolution during the melt season on an Arctic glacier is assessed using ground-based oblique-view cameras, spaceborne imaging and spaceborne RADAR. The repeated and systematic Synthetic Aperture RADAR (SAR) imaging by the European Space Agency’s Sentinel-1 spaceborne RADARs allows for all-weather, all-illumination condition monitoring of the snow-covered fraction of the glacier and hence assessing its water production potential. A comparison of the RADAR reflectivity with optical and multispectral imaging highlights the difference between the observed quantities—water content in the former, albedo in the latter—and the complementarity for understanding the snow melt processes. This work highlights the temporal inertia between the visible spring melting of the snowpack and the snow metamorphism. It was found that the snowpack exhibits that approximately 30 days before it starts to fade.
Urban Flood Resilience Evaluation Based on GIS and Multi-Source Data: A Case Study of Changchun City
Authors: Zhang Zhen , Zhang Jiquan , Zhang Yichen , Chen Yanan , Yan Jiahao
Published: March 2023

With extreme rainfall events and rapid urbanization, urban flood disaster events are increasing dramatically. As a key flood control city in China, Changchun City suffers casualties and economic losses every year due to floods. The improvement of flood resilience has become an important means for cities to resist flood risks. Therefore, this paper constructs an assessment model of urban flood resilience from four aspects: infrastructure, environment, society and economy. Then, it quantifies infrastructure and environmental vulnerability based on GIS, and uses TOPSIS to quantify social and economic recoverability. Finally, based on k-means clustering of infrastructure and environmental vulnerability and social and economic recoverability, the flood resilience of Changchun City was evaluated. The results show that different factors have different effects on flood resilience, and cities with low infrastructure and environmental vulnerability and high socioeconomic recoverability are more resilient in the face of floods. In addition, cities in the same cluster have the same flood resilience characteristics. The proposed framework can be extended to other regions of China or different countries by simply modifying the indicator system according to different regions, providing experience for regional flood mitigation and improving flood resilience.
Few-Shot PolSAR Ship Detection Based on Polarimetric Features Selection and Improved Contrastive Self-Supervised Learning
Authors: Qiu Weixing , Pan Zongxu , Yang Jianwei
Published: March 2023

Deep learning methods have been widely studied in the field of polarimetric synthetic aperture radar (PolSAR) ship detection over the past few years. However, the backscattering of manmade targets, including ships, is sensitive to the relative geometry between target orientation and radar line of sight, which makes the diversity of polarimetric and spatial features of ships. The diversity of scattering leads to a relative increase in the scarcity of PolSAR-labeled samples, which are difficult to obtain. To solve the abovementioned issue and extract the polarimetric and spatial features of PolSAR images better, this paper proposes a few-shot PolSAR ship detection method based on the combination of constructed polarimetric input data selection and improved contrastive self-supervised learning (CSSL) pre-training. Specifically, eight polarimetric feature extraction methods are adopted to construct deep learning network input data with polarimetric features. The backbone is pre-trained with un-labeled PolSAR input data through an improved CSSL method without negative samples, which enhances the representation capability by the multi-scale feature fusion module (MFFM) and implements a regularization strategy by the mix-up auxiliary pathway (MUAP). The pre-trained backbone is applied to the downstream ship detection network; only a few labeled samples are used for fine-tuning and the construction method of polarimetric input data with the best detection effect is studied. The comparison and ablation experiment results on the self-established PolSAR ship detection dataset verify the superiority of the proposed method, especially in the case of few-shot learning.
LiDAR-Derived Relief Typology of Loess Patches (East Poland)
Authors: Gawrysiak Leszek , Kociuba Waldemar
Published: March 2023

The application of the automated analysis of remote sensing data processed into high-resolution digital terrain models (DTMs) using geographic information systems (GIS) tools provides a geomorphometric characterization of the diversity of the relief of loess patches over large areas. Herein, a quantitative classification of 79 loess patches with a total area of 3361 km2, distributed within the eastern part of the Polish Uplands belt, is carried out. A high-resolution 1 × 1 m DTM was generated from airborne laser scanning (ALS) data with densities ranging from 4 pts/m2 to 12 pts/m2, which was resampled to a resolution of 5 × 5 m for the study. This model was used to classify landform surfaces using the r.geomorphon (geomorphon algorithm) function in GRASS GIS software. By comparing the values in the neighborhood of each cell, a map of geomorphometric features (geomorphon) was obtained. The classification and typology of the relief of the studied loess patches was performed using GeoPAT2 (Geospatial Pattern Analysis Toolbox) software. Pattern signatures with a resolution of 100 × 100 m were extracted from the source data grid, and the similarity of geomorphological maps within the signatures was calculated and saved as a signature file and segment map using the spatial coincidence method. The distance matrix between each pair of segments was calculated, and the heterogeneity and isolation of the maps were generated. R system was used to classify the segments, which generated a dendrogram and a heat map based on the distance matrix. This made it possible to distinguish three main types and eight subtypes of relief. The morphometric approach used will contribute to a better understanding of the spatial variation in the relief of loess patches.
Absolute and Relative Depth-Induced Network for RGB-D Salient Object Detection
Authors: Kong Yuqiu , Wang He , Kong Lingwei , Liu Yang , Yao Cuili , Yin Baocai
Published: March 2023

Detecting salient objects in complicated scenarios is a challenging problem. Except for semantic features from the RGB image, spatial information from the depth image also provides sufficient cues about the object. Therefore, it is crucial to rationally integrate RGB and depth features for the RGB-D salient object detection task. Most existing RGB-D saliency detectors modulate RGB semantic features with absolution depth values. However, they ignore the appearance contrast and structure knowledge indicated by relative depth values between pixels. In this work, we propose a depth-induced network (DIN) for RGB-D salient object detection, to take full advantage of both absolute and relative depth information, and further, enforce the in-depth fusion of the RGB-D cross-modalities. Specifically, an absolute depth-induced module (ADIM) is proposed, to hierarchically integrate absolute depth values and RGB features, to allow the interaction between the appearance and structural information in the encoding stage. A relative depth-induced module (RDIM) is designed, to capture detailed saliency cues, by exploring contrastive and structural information from relative depth values in the decoding stage. By combining the ADIM and RDIM, we can accurately locate salient objects with clear boundaries, even from complex scenes. The proposed DIN is a lightweight network, and the model size is much smaller than that of state-of-the-art algorithms. Extensive experiments on six challenging benchmarks, show that our method outperforms most existing RGB-D salient object detection models.
Managing Security of Healthcare Data for a Modern Healthcare System
Authors: Almalawi Abdulmohsen , Khan Asif Irshad , Alsolami Fawaz , Abushark Yoosef B. , Alfakeeh Ahmed S.
Published: March 2023

The advent of Artificial Intelligence (AI) and the Internet of Things (IoT) have recently created previously unimaginable opportunities for boosting clinical and patient services, reducing costs and improving community health. Yet, a fundamental challenge that the modern healthcare management system faces is storing and securely transferring data. Therefore, this research proposes a novel Lionized remora optimization-based serpent (LRO-S) encryption method to encrypt sensitive data and reduce privacy breaches and cyber-attacks from unauthorized users and hackers. The LRO-S method is the combination of hybrid metaheuristic optimization and improved security algorithm. The fitness functions of lion and remora are combined to create a new algorithm for security key generation, which is provided to the serpent encryption algorithm. The LRO-S technique encrypts sensitive patient data before storing it in the cloud. The primary goal of this study is to improve the safety and adaptability of medical professionals’ access to cloud-based patient-sensitive data more securely. The experiment’s findings suggest that the secret keys generated are sufficiently random and one of a kind to provide adequate protection for the data stored in modern healthcare management systems. The proposed method minimizes the time needed to encrypt and decrypt data and improves privacy standards. This study found that the suggested technique outperformed previous techniques in terms of reducing execution time and is cost-effective.
From Raising Awareness to a Behavioural Change: A Case Study of Indoor Air Quality Improvement Using IoT and COM-B Model
Authors: Kureshi Rameez Raja , Thakker Dhavalkumar , Mishra Bhupesh Kumar , Barnes Jo
Published: March 2023

The topic of indoor air pollution has yet to receive the same level of attention as ambient pollution. We spend considerable time indoors, and poorer indoor air quality affects most of us, particularly people with respiratory and other health conditions. There is a pressing need for methodological case studies focusing on informing households about the causes and harms of indoor air pollution and supporting changes in behaviour around different indoor activities that cause it. The use of indoor air quality (IAQ) sensor data to support behaviour change is the focus of our research in this paper. We have conducted two studies—first, to evaluate the effectiveness of the IAQ data visualisation as a trigger for the natural reflection capability of human beings to raise awareness. This study was performed without the scaffolding of a formal behaviour change model. In the second study, we showcase how a behaviour psychology model, COM-B (Capability, Opportunity, and Motivation-Behaviour), can be operationalised as a means of digital intervention to support behaviour change. We have developed four digital interventions manifested through a digital platform. We have demonstrated that it is possible to change behaviour concerning indoor activities using the COM-B model. We have also observed a measurable change in indoor air quality. In addition, qualitative analysis has shown that the awareness level among occupants has improved due to our approach of utilising IoT sensor data with COM-B-based digital interventions.
Performance Analysis of Wireless Communications with Nonlinear Energy Harvesting under Hardware Impairment and κ-μ Shadowed Fading
Authors: Le-Thanh Toi , Ho-Van Khuong
Published: March 2023

This paper improves energy efficiency and communications reliability for wireless transmission under κ-μ shadowed fading (i.e., integrating all channel impairments including path loss, shadowing, fading) and hardware impairment by employing a nonlinear energy harvester and multi-antenna power transmitter. To this end, this paper provides explicit formulas for outage probability. Numerous results corroborate these formulas and expose that energy-harvesting nonlinearity, hardware impairment, and channel conditions drastically deteriorate system performance. Notwithstanding, energy-harvesting nonlinearity influences system performance more severely than hardware impairment. In addition, desired system performance is accomplished flexibly and possibly by choosing a cluster of specifications. Remarkably, the proposed communications scheme obtains the optimal performance with the appropriate selection of the time-splitting factor.
Multi-Phase Fusion for Pedestrian Localization Using Mass-Market GNSS and MEMS Sensors
Authors: Liu Qiang , Ying Rendong , Dai Zhendong , Wang Yuze , Qian Jiuchao , Liu Peilin
Published: March 2023

Precise pedestrian positioning based on smartphone-grade sensors has been a research hotspot for several years. Due to the poor performance of the mass-market Micro-Electro-Mechanical Systems (MEMS) Magnetic, Angular Rate, and Gravity (MARG) sensors, the standalone pedestrian dead reckoning (PDR) module cannot avoid long-time heading drift, which leads to the failure of the entire positioning system. In outdoor scenes, the Global Navigation Satellite System (GNSS) is one of the most popular positioning systems, and smartphone users can use it to acquire absolute coordinates. However, the smartphone’s ultra-low-cost GNSS module is limited by some components such as the antenna, and so it is susceptible to serious interference from the multipath effect, which is a main error source of smartphone-based GNSS positioning. In this paper, we propose a multi-phase GNSS/PDR fusion framework to overcome the limitations of standalone modules. The first phase is to build a pseudorange double-difference based on smartphone and reference stations, the second phase proposes a novel multipath mitigation method based on multipath partial parameters estimation (MPPE) and a Double-Difference Code-Minus-Carrier (DDCMC) filter, and the third phase is to propose the joint stride lengths and heading estimations of the two standalone modules, to reduce the long-time drift and noise. The experimental results demonstrate that the proposed multipath error estimation can effectively suppress the double-difference multipath error exceeding 4 m, and compared to other methods, our fusion method achieves a minimum error RMSE of 1.63 m in positioning accuracy, and a minimum error RMSE of 4.71 m in long-time robustness for 20 min of continuous walking.
Designing of an Enhanced Fuzzy Logic Controller of an Interior Permanent Magnet Synchronous Generator under Variable Wind Speed
Authors: Masoud Uossif Mohamed Matoug , Tiwari Pratibha , Gupta Nishu
Published: March 2023

On account of active governmental stimulation operations in many countries, the residential production of electricity from renewable resources has increased considerably. Due to high efficiency and reliability, a recommended solution for residential wind energy conservation systems (WECS) is permanent magnet synchronous generators (PMSG). A higher torque ripple (TR), engendered by the contact of the stator with the rotor’s magnetomotive force harmonics, is one foremost issue in PMSGs. To control the synchronous generator, numerous control schemes have been proposed. However, it still faces a challenge in the diminishment of the TR. An enhanced fuzzy logic controller (EFLC) in interior PMSG (IPSMG) under variable wind speed (WS) has been proposed in this article to address this challenge. Initially, the wind turbine (WT) system was designed, and the IPMSG was proposed. A hysteresis controller (HC) and fuzzy logic controller (FLC) are the two controller types utilized in this model to control TR. This methodology used the EFLC to eliminate errors during the control. By using the proper membership function (MF) for boundary selection in the WDCSO algorithm, an enhancement was executed. Better performance in TR reduction was attained by the proposed model grounded in the analysis.
A Query-Based Network for Rural Homestead Extraction from VHR Remote Sensing Images
Authors: Wei Ren , Fan Beilei , Wang Yuting , Yang Rongchao
Published: March 2023

It is very significant for rural planning to accurately count the number and area of rural homesteads by means of automation. The development of deep learning makes it possible to achieve this goal. At present, many effective works have been conducted to extract building objects from VHR images using semantic segmentation technology, but they do not extract instance objects and do not work for densely distributed and overlapping rural homesteads. Most of the existing mainstream instance segmentation frameworks are based on the top-down structure. The model is complex and requires a large number of manually set thresholds. In order to solve the above difficult problems, we designed a simple query-based instance segmentation framework, QueryFormer, which includes an encoder and a decoder. A multi-scale deformable attention mechanism is incorporated into the encoder, resulting in significant computational savings, while also achieving effective results. In the decoder, we designed multiple groups, and used a Many-to-One label assignment method to make the image feature region be queried faster. Experiments show that our method achieves better performance (52.8AP) than the other most advanced models (+0.8AP) in the task of extracting rural homesteads in dense regions. This study shows that query-based instance segmentation framework has strong application potential in remote sensing images.
Editorial—Special Issue on “Optical and RF Atmospheric Propagation”
Authors: Kopeika Natan , Raj A Arockia Bazil
Published: March 2023

This Special Issue presents the latest research and developments in the field of optical and RF propagation sensing, propagation/effects/channel molding, advancements in applications, signal far-field measurements, theoretical/measurement methods for beam handling/processing, military applications, and next-generation network formations, amongst others [...]
Waste Detection System Based on Data Augmentation and YOLO_EC
Authors: Fan Jinhao , Cui Lizhi , Fei Shumin
Published: March 2023

The problem of waste classification has been a major concern for both the government and society, and whether waste can be effectively classified will affect the sustainable development of human society. To perform fast and efficient detection of waste targets in the sorting process, this paper proposes a data augmentation + YOLO_EC waste detection system. First of all, because of the current shortage of multi-objective waste classification datasets, the heavy workload of human data collection, and the limited improvement of data features by traditional data augmentation methods, DCGAN (deep convolution generative adversarial networks) was optimized by improving the loss function, and an image-generation model was established to realize the generation of multi-objective waste images; secondly, with YOLOv4 (You Only Look Once version 4) as the basic model, EfficientNet is used as the backbone feature extraction network to realize the light weight of the algorithm, and at the same time, the CA (coordinate attention) attention mechanism is introduced to reconstruct the MBConv module to filter out high-quality information and enhance the feature extraction ability of the model. Experimental results show that on the HPU_WASTE dataset, the proposed model outperforms other models in both data augmentation and waste detection.
Highly Efficient Refractive Index Sensor Based on a Dual-Side Polished SMS Fiber Enabled by Femtosecond Laser Writing
Authors: Li Jinke , Jiang Shiru , Aberdeen Stuart , Lee Sang-Shin
Published: March 2023

Fiber-optic refractive index (RI) sensors based on wavelength-shift-based interrogation continue to present a challenge in achieving high sensitivity for a wide detection range. In this paper, we propose a sensor for determining the RI of liquids based on femtosecond laser (fs-laser) writing of a dual-side polished singlemode–multimode–singlemode (SMS) fiber. The proposed sensor can determine the RI value of a surrounding liquid by detecting the dip wavelength in the transmission spectrum of the light propagating through the sensing area. The high RI sensitivity is attributed to the increased interaction area established by the fs-laser, which creates hydrophilic surfaces and maintains the wide detection range of the SMS structure. The results of the wavelength-shift-based interrogation reveal that the fabricated device exhibited a high sensitivity of 161.40 nm per refractive index unit (RIU) over a wide RI detection range of 0.062 RIU. The proposed device has high processing accuracy and a simple manufacturing process. Hence, it has the potential to be used as a lab-on-fiber sensing platform in chemical and biotechnological applications.
Assessment of a 16-Channel Ambulatory Dry Electrode EEG for Remote Monitoring
Authors: Shivaraja Theeban Raj , Remli Rabani , Kamal Noorfazila , Wan Zaidi Wan Asyraf , Chellappan Kalaivani
Published: March 2023

Ambulatory EEGs began emerging in the healthcare industry over the years, setting a new norm for long-term monitoring services. The present devices in the market are neither meant for remote monitoring due to their technical complexity nor for meeting clinical setting needs in epilepsy patient monitoring. In this paper, we propose an ambulatory EEG device, OptiEEG, that has low setup complexity, for the remote EEG monitoring of epilepsy patients. OptiEEG’s signal quality was compared with a gold standard clinical device, Natus. The experiment between OptiEEG and Natus included three different tests: eye open/close (EOC); hyperventilation (HV); and photic stimulation (PS). Statistical and wavelet analysis of retrieved data were presented when evaluating the performance of OptiEEG. The SNR and PSNR of OptiEEG were slightly lower than Natus, but within an acceptable bound. The standard deviations of MSE for both devices were almost in a similar range for the three tests. The frequency band energy analysis is consistent between the two devices. A rhythmic slowdown of theta and delta was observed in HV, whereas photic driving was observed during PS in both devices. The results validated the performance of OptiEEG as an acceptable EEG device for remote monitoring away from clinical environments.
PV Panel Model Parameter Estimation by Using Neural Network
Authors: Lo Wai Lun , Chung Henry Shu Hung , Hsung Richard Tai Chiu , Fu Hong , Shen Tak Wai
Published: March 2023

Photovoltaic (PV) panels have been widely used as one of the solutions for green energy sources. Performance monitoring, fault diagnosis, and Control of Operation at Maximum Power Point (MPP) of PV panels became one of the popular research topics in the past. Model parameters could reflect the health conditions of a PV panel, and model parameter estimation can be applied to PV panel fault diagnosis. In this paper, we will propose a new algorithm for PV panel model parameters estimation by using a Neural Network (ANN) with a Numerical Current Prediction (NCP) layer. Output voltage and current signals (VI) after load perturbation are observed. An ANN is trained to estimate the PV panel model parameters, which is then fined tuned by the NCP to improve the accuracy to about 6%. During the testing stage, VI signals are input into the proposed ANN-NCP system. PV panel model parameters can then be estimated by the proposed algorithms, and the estimated model parameters can be then used for fault detection, health monitoring, and tracking operating points for MPP conditions.
Joint Method of Moments (JMoM) and Successive Moment Cancellation (SMC) Multiuser Time Synchronization for ZP-OFDM-Based Waveforms Applicable to Joint Communication and Sensing
Authors: Pourtahmasi Roshandeh Koosha , Mohammadkarimi Mostafa , Ardakani Masoud
Published: March 2023

It has been recently shown that zero padding (ZP)-orthogonal frequency-division multiplexing (OFDM) is a promising candidate for 6G wireless systems requiring joint communication and sensing. In this paper, we consider a multiuser uplink scenario where users are separated in power domain, i.e., non-orthogonal multiple access (NOMA), and use ZP-OFDM signals. The uplink transmission is grant-free and users are allowed to transmit asynchronously. In this setup, we address the problem of time synchronization by estimating the timing offset (TO) of all the users. We propose two non-data-aided (NDA) estimators, i.e., the joint method of moment (JMoM) and the successive moment cancellation (SMC), that employ the periodicity of the second order moment (SoM) of the received samples for TO estimation. Moreover, the coding assisted (CA) version of the proposed estimators, i.e., CA-JMoM and CA-SMC, are developed for the case of short observation samples. We also extend the proposed estimators to multiuser multiple-input multiple-output (MIMO) systems. The effectiveness of the proposed estimators is evaluated in terms of lock-in probability under various practical scenarios. Simulation results show that the JMoM estimator can reach the lock-in probability of one for the moderate range of Eb/N0 values. While existing NDA TO estimators in the literature either offer low lock-in probability, high computational complexity that prevents them from being employed in MIMO systems, or are designed for single-user scenarios, the proposed estimators in this paper address all of these issues.
Reading Health and the Reading Health Index
Authors: Gerčar Jaka , van der Weel Adriaan
Published: March 2023

This paper introduces Reading Health as a concept to help chart the collective reading habits of the individuals that make up a society—at any aggregate level. Now that the digital medium is transforming reading practices, and particularly the position of paper books and longform reading in society, the authors suggest a thorough examination of prevalent assumptions about reading and a fresh formulation of explicit reading aims for the future. The concept of Reading Health (RH) is paired with a corresponding Reading Health Index (RHI), an instrument to benchmark and keep track of changes in a society’s Reading Health over time.
Political Hierarchy of Opening-Up Policy and China’s Carbon Reduction: Empirical Research Based on Spatial Regression Discontinuity
Authors: Zhang Nan , Zhuang Yan
Published: March 2023

This paper constructs a counterfactual framework based on the opening-up policies of provinces in the eastern coastal region. It analyzes the role of the political hierarchy of the opening-up policy in China’s carbon reduction at the county level by using Spatial Regression Discontinuity, and the data used are from 1997 to 2017. The study found the following: (1) The improvement of the political hierarchy of the opening-up policy is negatively related to the carbon reduction, which has significantly boosted the carbon emission of counties in the eastern coastal areas of China. (2) The impact on border counties is more significant, and there is an obvious boundary effect. In terms of net carbon emissions, the political-hierarchy difference has a significant impact only in the area adjacent to the border. (3) There is strong heterogeneity among provinces, showing the boundary jump effect and boundary depression effect. (4) The political-hierarchy differences are significantly related to the regional carbon reduction by changing policy intensity, resulting in fiscal subsidies effects and gradient transfer effects. The location selection for the implementation of the opening-up policy significantly impacted the carbon reductions.
Utilization of Stockwell Transform, Support Vector Machine and D-STATCOM for the Identification, Classification and Mitigation of Power Quality Problems
Authors: Mengistu Epaphros , Khan Baseem , Qasaymeh Yazeed , Alghamdi Ali S. , Zubair Muhammad , Awan Ahmed Bilal , Ashiq Muhammad Gul Bahar , Ali Samia Gharib , Pérez-Oleaga Cristina Mazas
Published: March 2023

Power Quality (PQ) has become a significant issue in power networks. Power quality disturbances must be precisely and appropriately identified. This activity involves identifying, classifying, and mitigating power quality problems. A case study of the Awada industrial zone in Ethiopia is taken into consideration to show the practical applicability of the proposed work. It is found that the current harmonic distortion levels exceed the restrictions with a maximum percentage Total Harmonic Distortion of Current (THDI) value of up to 23.09%. The signal processing technique, i.e., Stockwell Transform (ST) is utilized for the identification of power quality issues, and it covers the most important and common power quality issues. The Support Vector Machine (SVM) method is used to categorize power quality issues, which enhances the classification procedure. The ST scored better in terms of accuracy than the Wavelet Transform (WT), Fourier Transform (FT), and Hilbert Transform (HT), obtaining 97.1%, as compared to 91.08%, 88.91%, and 86.8%, respectively. The maximum classification accuracy of SVM was 98.3%. To lower the current level of harmonic distortion in the industrial sector, a Distribution Static Compensator (D-STATCOM) is developed in the current control mode. To evaluate the performance of the D-STATCOM, the performance of the distribution network with and without D-STATCOM is simulated. The simulation results show that THDI is reduced to 4.36% when the suggested D-STATCOM is applied in the system.
A Mixed-Method Approach to Determine the Successful Factors Affecting the Criticality Level of Intermediate and Final Products on National Basis: A Case Study from Saudi Arabia
Authors: Fadil Aiman , Davis Paul , Geraghty John
Published: March 2023

COVID-19, Brexit, war, and some other similar cases will leave/have left us with a lesson that has had an impact on the supply chains of almost all product types. Countries have now recognized that some products cannot be sustained in a situation of uncertainty. This research covers the gap in understanding and identifying the successful factors affecting the criticality level of supply required of intermediate and final products (IFP) at the national level. It investigates the relationship between two factors: the casual factor supply risk (independent factor); and the impacted (dependent factors) political, economic, sociocultural, and technological (PEST) factors in terms of identifying critical products using the principle of Resource Dependency Theory (RDT). A literature review was conducted, followed by a mixed-method approach. Semi-structured interviews with 23 Saudi experts were carried out initially; then, a questionnaire was shared with 152 Saudi experts in different sectors. The qualitative study identified 30 key measurement variables for both factors, in which 19 variables were confirmed using the factor analysis (FA) technique.