bluuebunny/crossref_metadata_2025 huggingface dataset:
Tribo-Mechanical Investigation of Glass Fiber Reinforced Polymer Composites under Dry Conditions
Authors: Birleanu Corina , Pustan Marius , Cioaza Mircea , Bere Paul , Contiu Glad , Dudescu Mircea Cristian , Filip Daniel
Published: June 2023

Tribo-mechanical experiments were performed on Glass Fiber Reinforced Polymer (GRFP) composites against different engineering materials, and the tribological behavior of these materials under dry conditions was investigated. The novelty of this study consists of the investigation of the tribomechanical properties of a customized GFRP/epoxy composite, different from those identified in the literature. The investigated material in the work is composed of 270 g/m2 fiberglass twill fabric/epoxy matrix. It was manufactured by the vacuum bag method and autoclave curing procedure. The goal was to define the tribo-mechanical characteristics of a 68.5% weight fraction ratio (wf) of GFRP composites in relation to the different categories of plastic materials, alloyed steel, and technical ceramics. The properties of the material, including ultimate tensile strength, Young’s modulus of elasticity, elastic strain, and impact strength of the GFPR, were determined through standard tests. The friction coefficients were obtained using a modified pin-on-disc tribometer using sliding speeds ranging from 0.1 to 0.36 m s−1, load 20 N, and different counter face balls from Polytetrafluoroethylene (PTFE), Polyamide (Torlon), 52,100 Chrome Alloy Steel, 440 Stainless Steel, and Ceramic Al2O3, with 12.7 mm in diameter, in dry conditions. These are commonly used as ball and roller bearings in industry and for a variety of automotive applications. To evaluate the wear mechanisms, the worm surfaces were examined and investigated by a Nano Focus—Optical 3D Microscopy, which uses cutting-edge μsurf technology to provide highly accurate 3D measurements of surfaces. The obtained results constitute an important database for the tribo-mechanical behavior of this engineering GFRP composite material.
Study of Heat Treatment Effect on Mechanical Properties of Epoxy Resin Reinforced with Fiber Glass
Authors: Lan Zhenbo , Deng Jiangang , Xu Zhuolin , Ye Zhu , Nie Yu
Published: June 2023

In this paper, mechanical properties of the diglycidyl ether of bisphenol A epoxy resin (EP) reinforced with a 20% fiber glass (GF) with layered structure after high temperature aging are studied. Tensile and flexural stress–strain curves of the GF/EP composite after aging tests in the temperature range of 85–145 °C in air were measured. Tensile and flexural strength demonstrate gradual decrease with the increase in the aging temperature. The failure mechanism at the micro scale is studied by the scanning electron microscopy. A separation of the GFs and EP matrix and evident pullout of the GFs are observed. Degradation of the mechanical properties is explained by a cross-linking and chain scission of the initial molecular structure of the composite and decrease in the interfacial adhesion force between GFs and EP matrix caused by oxidation of the EP matrix and difference of the GF and EP coefficients of thermal expansion.
Overview of Solar Steam Devices from Materials and Structures
Authors: Liu Chang , Yin Zhenhao , Hou Yue , Yin Chengri , Yin Zhenxing
Published: June 2023

The global shortage of freshwater supply has become an imminent problem. The high energy consumption of traditional desalination technology cannot meet the demand for sustainable energy development. Therefore, exploring new energy sources to obtain pure water has become one of the effective ways to solve the freshwater resource crisis. In recent years, solar steam technology which utilizes solar energy as the sole input source for photothermal conversion has shown to be sustainable, low-cost, and environmentally friendly, providing a viable low-carbon solution for freshwater supply. This review summarizes the latest developments in solar steam generators. The working principle of steam technology and the types of heating systems are described. The photothermal conversion mechanisms of different materials are illustrated. Emphasis is placed on describing strategies to optimize light absorption and improve steam efficiency from material properties to structural design. Finally, challenges in the development of solar steam devices are pointed out, aiming to provide new ideas for the development of solar steam devices and alleviate the shortage of freshwater resources.
Scheduling Jobs with a Limited Waiting Time Constraint on a Hybrid Flowshop
Authors: Shim Sang-Oh , Jeong BongJoo , Bang June-Yong , Park JeongMin
Published: June 2023

In this paper, we address a two-stage hybrid flowshop scheduling problem with identical parallel machines in each stage. The problem assumes that the queue (Q)-time for each job, which represents the waiting time to be processed in the current stage, must be limited to a predetermined threshold due to quality concerns for the final product. This problem is motivated by one that occurs in the real field, especially in the diffusion workstation of a semiconductor fabrication. Our objective is to minimize the makespan of the jobs while considering product quality. To achieve this goal, we formulated mathematical programming, developed two dominance properties for this problem, and proposed three heuristics with the suggested dominance properties to solve the considered problem. We conducted simulation experiments to evaluate the performance of the proposed approaches using randomly generated problem instances that are created to closely resemble real production scenarios, and the results demonstrate their superiority over existing methods. Furthermore, we applied the proposed methods in a real-world setting within the semiconductor fabrication industry, where they have exhibited better performance compared to the dispatching rules commonly used in practical applications. These findings validate the effectiveness and applicability of our proposed methodologies in real-world scenarios.
D-Limonene as a Promising Green Solvent for the Detachment of End-of-Life Photovoltaic Solar Panels under Sonication
Authors: Abdo Dina Magdy , Mangialardi Teresa , Medici Franco , Piga Luigi
Published: June 2023

Consumption of photovoltaic solar panels is expected to increase, so the growing amount of end-of-life (EOL) solar panels will require large spaces for their disposal, which at the moment costs around 200 euros/ton. Thus, a proper treatment technique to recover secondary materials from this waste, which are mainly copper, aluminum, silicon, high-transmittance glass, and plastics, must be developed. The last three components are strongly attached to each other; hence, their detachment is necessary for recovery. To achieve this objective, a chemical route was chosen; in fact, solvent extraction is highly recommended, as it has a high separation efficiency. In this study, D-limonene as a bio-solvent was examined for detaching different components of solar panels from each other. A high efficiency for ethylene vinyl acetate (EVA) dissolution and components’ detachment under different conditions was achieved with the help of sonication power. The effects of sonication power, thermal pre-treatment, temperature, and contact time on detachment percentage were examined, and the best conditions (namely, no pre-treatment, medium sonication power of 450 W, temperature of 60 °C, and a contact time of 120 min) were found for total component detachment. Additionally, the recyclability of D-limonene was examined, and it was established that the solvent could carry out 100% component detachment for three cycles.
Existing Stature and Possible Outlook of Renewable Power in Comprehensive Electricity Market
Authors: Das Shreya Shree , Kumar Jayendra , Dawn Subhojit , Salata Ferdinando
Published: June 2023

The massive growth in power demand and the sharp decay in the availability of conventional energy sources forces society to move toward renewable power consumption. The rise in renewable energy utilization is one of the greatest strategies involved in making the environment clean, green, and emission-free. The investment cost is slightly high for this kind of resource, but their running costsare very minimal, which encourages power producers to invest in renewable power plants. Power producers always focus on their economic profit and possible feasibilities before the investment in a new power plant setup. Wind, small hydro, and solar photovoltaics have been considered the foremost efficient and feasible renewable sources. In 2021, the worldwide renewable power capacity had grown to 17%, despite supply chain disturbances and surges in prices. The renewable power market set a target of achieving a 95% increment in global power capacity by 2026. Hence, humankind should consider wind, hydro, and solar photovoltaics as the main energy sources, and there is a need to increase use of such sources. This paper highlights the latest developments, enormous technologies, and upcoming aspects of wind power, hydropower, and solar photovoltaics in India, as well as around the globe. The present status of renewable energy can motivate global power producers to spend their money on the installation of a new renewable power plant to obtain more economic benefits and give societal economic and environmental payback to humans.
Valuation of Plastic Waste as a Community Circular Economy Strategy in the Municipality of Choco–Colombia
Authors: Ortega-Ramírez Angie Tatiana , Reyes Tovar Miriam , del Carmen Elmira Castro Nelly , Silva-Marrufo Oscar
Published: June 2023

A business solution is proposed for the accumulation of waste in the Municipality of Choco without prior treatment through the establishment of a center for the reception, classification, recovery and use of solid plastic waste in the Municipality of Quibdo, which would optimize and expand the management of plastic waste. In this study, the basic diagnosis of the practices that are currently carried out in Quibdo is evaluated with the appropriation of the knowledge of the population, the technical structuring of the conditions of production of plastic wood is carried out from the management of plastic waste, recognition of the market for waste generated as an alternative for development and sustainable growth and the financial feasibility of the project and the profitability of each of the investment plans for its implementation. The results of the investigation include the identification of weaknesses and opportunities in waste management practices and the proposal of two investment plans for the establishment of the center. It is concluded that investment plan 2 would require 46,590.50 USD less than investment plan 1, equivalent to a 2.21% return compared to investment plan 1.
The Neglected Place of “Totems” in Contemporary Art
Authors: Zhang Aixin
Published: June 2023

The religious nature of Joseph Beuys’ works was ignored or intentionally avoided by mainstream criticism since his artistic practice was ridiculed for its potential spirituality. It is argued that Beuys’ works are work meditations on the issues of potential ego in totemic art, which are frequent topics of theological concern. For example, what is the nature of our consciousness after death, and how does it relate to the consciousness of others? Beuys’ conceptual artworks reveal his engagement with the “witchcraft etiquette” of totemic art and his exploration of theological questions such as the relation between human consciousness and divinity, the role of sacrifice and resurrection, and the meaning of self-awareness. In other words, we can draw inspiration from the theological theories of Alfred North Whitehead and Georg Wilhelm Friedrich Hegel to examine Beuys’ choice of conceptual art through the lens of his deep self-consciousness of totem worship. In general, Beuys’ works pose an important question: how can we awaken our chaotic consciousness to new or forgotten sprouts which may rejuvenate our existence in the world?
Belonging to the City: Alliances between Community Art and Diaconia as a Means to Overcome Segregation in a Gentrifying Neighbourhood in Amsterdam
Authors: Meijers Erica
Published: June 2023

Between 2019 and 2021, volunteers of a local Protestant congregation in Amsterdam, professional artists, and (other) local residents organised the interactive exhibit A(t) home in the Staats. In this project, community art and diaconia joined forces using multidisciplinary methods to strengthen relations in the neighbourhood and to discern issues of belonging and lines of division in the changing neighbourhood. The project was situated at the intersection of an “up and coming” neighbourhood and a shrinking congregation. By analysing the exhibit, this article contributes to the development of creative, arts-based research methods in diaconal studies. Within this approach, art is never a mere illustration or a vehicle for reflection but rather a generator of knowledge. The central question is: how can alliances between community art and diaconia contribute to overcoming segregation in urban contexts? This question is informed by the process of gentrification and the search by city churches for ways to engage with urban changes. After the introduction and methodological reflections, the article describes the background and practice of the project, followed by the outcomes of the interactive exhibit. It concludes by answering the central question and mapping theoretical and practical challenges concerning alliances between art and diaconia in urban contexts.
Morphology Dynamics of Ice Cover in a River Bend Revealed by the UAV-GPR and Sentinel-2
Authors: Li Chunjiang , Li Zhijun , Huang Wenfeng , Zhang Baosen , Deng Yu , Li Guoyu
Published: June 2023

After the formation of the bend ice cover, the ice thickness of the bend is not uniformly distributed, and an open-water area is usually formed downstream of the bend. The spatial and temporal variation of the ice thickness in seven cross sections was determined via Unmanned Aerial Vehicle Ground Penetrating Radar (UAV-GPR) technology and traditional borehole measurements. The plane morphology change of the open water was observed by Sentinel-2. The results show that the average dielectric permittivity of GPR was 3.231, 3.249, and 3.317 on three surveys (5 January 2022, 16 February 2022, and 25 February 2022) of the Yellow River ice growing period, respectively. The average ice thickness of the three surveys was 0.402 m, 0.509 m, and 0.633 m, respectively. The ice thickness of the concave bank was larger than that of the convex bank. The plane morphology of the open water first shrinks rapidly longitudinally and then shrinks slowly transversely. The vertical boundary of the open water was composed of two arcs, in which the slope of Arc I (close to the water surface) was steeper than that of Arc II, and the hazardous distance of the open-water boundary was 10.3 m. The increased flow mostly affected the slope change of Arc I. Finally, we discuss the variation of hummocky ice and flat ice in GPR images and the physical factors affecting GPR detection accuracy, as well as the ice-thickness variation of concave and convex banks in relation to channel curvature.
A Proposal for Automatic Coastline Extraction from Landsat 8 OLI Images Combining Modified Optimum Index Factor (MOIF) and K-Means
Authors: Figliomeni Francesco Giuseppe , Guastaferro Francesca , Parente Claudio , Vallario Andrea
Published: June 2023

The coastal environment is a natural and economic resource of extraordinary value, but it is constantly modifying and susceptible to climate change, human activities and natural hazards. Remote sensing techniques have proved to be excellent for coastal area monitoring, but the main issue is to detect the borderline between water bodies (ocean, sea, lake or river) and land. This research aims to define a rapid and accurate methodological approach, based on the k-means algorithm, to classify the remotely sensed images in an unsupervised way to distinguish water body pixels and detect coastline. Landsat 8 Operational Land Imager (OLI) multispectral satellite images were considered. The proposal requires applying the k-means algorithm only to the most appropriate multispectral bands, rather than using the entire dataset. In fact, by using only suitable bands to detect the differences between water and no-water (vegetation and bare soil), more accurate results were obtained. For this scope, a new index based on the optimum index factor (OIF) was applied to identify the three best-performing bands for the purpose. The direct comparison between the automatically extracted coastline and the manually digitized one was used to evaluate the product accuracy. The results were very satisfactory and the combination involving bands B2 (blue), B5 (near infrared), and B6 (short-wave infrared-1) provided the best performance.
Correction: Sesnie et al. In-Situ and Remote Sensing Platforms for Mapping Fine-Fuels and Fuel-Types in Sonoran Semi-Desert Grasslands. Remote Sens. 2018, 10, 1358
Authors: Sesnie Steven E. , Eagleston Holly , Johnson Lacrecia , Yurcich Emily
Published: June 2023

Text Correction [...]
Accuracy Assessment of Eleven Medium Resolution Global and Regional Land Cover Land Use Products: A Case Study over the Conterminous United States
Authors: Wang Zhixin , Mountrakis Giorgos
Published: June 2023

Land cover land use (LCLU) products provide essential information for numerous environmental and human studies. Here, we assess the accuracy of eleven global and regional products over the conterminous U.S. using 25,000 high-confidence randomly distributed samples. Results show that in general, the National Land Cover Database (NLCD) and the Land Change Monitoring, Assessment and Projection (LCMAP) outperform other multi-class products, both in terms of higher individual class accuracy and with accuracy variability across classes. More specifically, F1 accuracy comparisons between the best performing USGS and non-USGS products indicate: (i) similar performance for the water class, (ii) USGS product outperformance in the developed (+1.3%), grass/shrub (+3.2%) and tree cover (+4.2%) classes, and (iii) non-USGS product (WorldCover) gains in the cropland (+5.1%) class. The NLCD and LCMAP also outperformed specialized single-class products, such as the Hansen Global Forest Change, the Cropland Data Layer and the Global Artificial Impervious Areas, while offering comparable results to the Global Surface Water Dynamics product. Spatial visualizations also allowed accuracy comparisons across different geographic areas. In general, the NLCD and LCMAP have disagreements mainly in the middle and southeastern part of conterminous U.S. while Esri, WorldCover and Dynamic World have most errors in the western U.S. Comparisons were also undertaken on a subset of the reference data, called spatial edge samples, that identifies samples surrounded by neighboring samples of different class labels, thus excluding easy-to-classify homogenous areas. There, the WorldCover product offers higher accuracies for the highly dynamic grass/shrub (+4.4%) and cropland (+8.1%) classes when compared to the NLCD and LCMAP products. An important conclusion while looking at these challenging samples is that except for the tree class (78%), the best performing products per class range in accuracy between 55% and 70%, which suggests that there is substantial room for improvement.
Sensitivity of Grassland Coverage to Climate across Environmental Gradients on the Qinghai-Tibet Plateau
Authors: Wu Rihan , Hu Guozheng , Ganjurjav Hasbagan , Gao Qingzhu
Published: June 2023

Grassland cover is strongly influenced by climate change. The response of grassland cover to climate change becomes complex with background climate. There have been some advances in research on the sensitivity of grassland vegetation to climate change around the world, but the differences in climate sensitivity among grassland types are still unclear in alpine grassland. Therefore, we applied MODIS NDVI data and trend analysis methods to quantify the spatial and temporal variation of grassland vegetation cover on the Qinghai-Tibet Plateau. Then, we used multiple regression models to analyze the sensitivity of fractional vegetation cover (FVC) to climatic factors (Temperature, Precipitation, Solar radiation, Palmer drought severity index) and summarized the potential mechanisms of vegetation sensitivity to different climatic gradients. Our results showed (1) a significant increasing trend in alpine desert FVC from 2000–2018 (1.12 × 10−3/a, R2 = 0.56, p < 0.001) but no significant trend in other grassland types. (2) FVC sensitivity to climatic factors varied among grassland types, especially in the alpine desert, which had over 60% of the area with positive sensitivity to temperature, precipitation and PDSI. (3) The sensitivity of grassland FVC to heat factors decreases with rising ambient temperature while the sensitivity to moisture increases. Similarly, the sensitivity to moisture decreases while the sensitivity to thermal factors increases along the moisture gradient. Furthermore, the results suggest that future climate warming will promote grassland in cold and wet areas of the Qinghai-Tibet Plateau and may suppress vegetation in warmer areas. In contrast, the response of the alpine desert to future climate is more stable. Studying the impact of climate variation at a regional scale could enhance the adaptability of vegetation in future global climates.
Estimating the Evolution of a Post-Little Ice Age Deglaciated Alpine Valley through the DEM of Difference (DoD)
Authors: Azzoni Roberto Sergio , Pelfini Manuela , Zerboni Andrea
Published: June 2023

Since the end of the Little Ice Age (LIA, ~1830), the accelerated glaciers’ shrinkage along mid-latitude high mountain areas promoted a quick readjustment of geomorphological processes with the onset of the paraglacial dynamic, making proglacial areas among the most sensitive Earth’s landscapes to ongoing climate change. A potentially useful remote-sensing method for investigating such dynamic areas is the DEM (Digital Elevation Model) of Difference (DoD) technique, which quantifies volumetric changes in a territory between successive topographic surveys. After a detailed geomorphological analysis and comparison with historical maps of the Martello Valley (central Italian Alps), we applied the DoD for reconstructing post-LIA deglaciation dynamics and reported on the surface effects of freshly-onset paraglacial processes. The head of the valley is still glacierized, with three main ice bodies resulting from the huge reduction of a single glacier present at the apogee of the LIA. Aftermath: the glaciers lose 60% of their initial surface area, largely modifying local landforms and expanding the surface of the proglacial areas. The DoD analysis of the 2006–2015 timeframe (based on registered DEM derived from LiDAR—Light Detection and Ranging—data) highlights deep surface elevation changes ranging from +38 ± 4.01 m along the foot of rock walls, where gravitative processes increased their intensity, to −47 ± 4.01 m where the melting of buried ice caused collapses of the proglacial surface. This approach permits estimating the volume of sediments mobilized and reworked by paraglacial processes. Here, in less than 10 years, −23,675 ± 1165 m3 of sediment were removed along the proglacial area and transported down valley, highlighting the dynamicity of proglacial areas.
Applying Reconstructed Daily Water Storage and Modified Wetness Index to Flood Monitoring: A Case Study in the Yangtze River Basin
Authors: Xiao Cuiyu , Zhong Yulong , Wu Yunlong , Bai Hongbing , Li Wanqiu , Wu Dingcheng , Wang Changqing , Tian Baoming
Published: June 2023

The terrestrial water storage anomaly (TWSA) observed by the Gravity Recovery and Climate Experiment (GRACE) satellite and its successor GRACE Follow-On (GRACE-FO) provides a new means for monitoring floods. However, due to the coarse temporal resolution of GRACE/GRACE-FO, the understanding of flood occurrence mechanisms and the monitoring of short-term floods are limited. This study utilizes a statistical model to reconstruct daily TWS by combining monthly GRACE observations with daily temperature and precipitation data. The reconstructed daily TWSA is utilized to monitor the catastrophic flood event that occurred in the middle and lower reaches of the Yangtze River basin in 2020. Furthermore, the study compares the reconstructed daily TWSA with the vertical displacements of eight Global Navigation Satellite System (GNSS) stations at grid scale. A modified wetness index (MWI) and a normalized daily flood potential index (NDFPI) are introduced and compared with in situ daily streamflow to assess their potential for flood monitoring and early warning. The results show that terrestrial water storage (TWS) in the study area increases from early June, reaching a peak on 19 July, and then receding till September. The reconstructed TWSA better captures the changes in water storage on a daily scale compared to monthly GRACE data. The MWI and NDFPI based on the reconstructed daily TWSA both exceed the 90th percentile 7 days earlier than the in situ streamflow, demonstrating their potential for daily flood monitoring. Collectively, these findings suggest that the reconstructed TWSA can serve as an effective tool for flood monitoring and early warning.
Characteristics of Regional GPS Crustal Deformation before the 2021 Yunnan Yangbi Ms 6.4 Earthquake and Its Implications for Determining Potential Areas of Future Strong Earthquakes
Authors: Dai Chenglong , Gan Weijun , Li Zhangjun , Liang Shiming , Xiao Genru , Zhang Keliang , Zhang Ling
Published: June 2023

The 2021 Yangbi Ms 6.4 earthquake in Yunnan, China, occurred in an area where the Global Positioning System (GPS) geodetic observations are particularly intensive. Based on a detailed retrospective analysis of the GPS observations of about 133 stations distributed in the proximately 400 km × 400 km region that contains the area affected by the earthquake., we obtain a high-resolution GPS velocity field and strain rate field and then derive the present-day slip rates of major faults in the region with the commonly used half-space elastic dislocation model and constraints from the GPS velocity field. Furthermore, by calculating the seismic moment accumulation and release and deficit rates in the main fault segments and combining with the distribution characteristics of small earthquakes, we evaluate the regional seismic risk. The results show that (1) there was a localized prominent strain accumulation rate around the seismogenic area of the impending Yangbi Ms 6.4 earthquake, although this was not the only area with a prominent strain rate in the whole region. (2) The seismogenic area of the earthquake was just located where the strain direction was deflected, which, together with the localized outstanding maximum shear strain and dilatation rates, provides us with important hints to determine the potential areas of future strong earthquakes. (3) Of all the seismogenic fault segments with relatively high potentials, judged using the elapsed time of historical earthquakes and effective strain accumulation rate, the middle section of the Weixi–Qiaohou fault has a higher earthquake risk than the southern section, the Midu–Binchuan section of the Chenghai fault has a higher risk than the Yongsheng section and the Jianchuan section of the Jianchuan–Qiaohou–Lijiang–Xiaojinhe fault has a higher risk than the Lijiang section.
Three-Dimensional Tracking of a Target under Angle-Frequency Measurements with Multiple Frequency Lines
Authors: Kim Jonghoek
Published: June 2023

This article considers tracking a constant-velocity underwater target, which emits sound with distinct frequency lines. By analyzing the target’s azimuth, elevation and multiple frequency lines, the ownship can estimate the target’s position and (constant) velocity. In our paper, this tracking problem is called the 3D Angle-Frequency Target Motion Analysis (AFTMA) problem. We consider the case where some frequency lines disappear and appear occasionally. Instead of tracking every frequency line, this paper proposes to estimate the average emitting frequency by setting the average frequency as the state vector in the filter. As the frequency measurements are averaged, the measurement noise decreases. In the case where we use the average frequency line as our filter state, both the computational load and the root mean square error (RMSE) decrease, compared to the case where we track every frequency line one by one. As far as we know, our manuscript is unique in addressing 3D AFTMA problems, such that an ownship can track an underwater target while measuring the target’s sound with multiple frequency lines. The performance of the proposed 3D AFTMA filter is demonstrated utilizing MATLAB simulations.
Prediction of Cable Behavior Using Finite Element Analysis Results for Flexible Cables
Authors: Kim Hyeonjin , Kim Jinhyun
Published: June 2023

In actual industrial sites, verifying the framework for cable manipulation is crucial. Therefore, it is necessary to simulate the deformation of the cable to predict its behavior accurately. By simulating the behavior in advance, it is possible to reduce the time and cost required for work. Although finite element analysis is used in various fields, the results may differ from the actual behavior depending on the method of defining the analysis model and analysis conditions. This paper aims to select appropriate indicators that can effectively cope with finite element analysis and experiments during cable winding work. We perform finite element analysis of the behavior of flexible cables and compare the analysis results with results from experiments. Despite some differences between the experimental and analysis outcomes, an indicator was developed through trial and error to align the two cases. Errors occurred during the experiments depending on the analysis and experimental conditions. To address this, weights were derived through optimization to update the cable analysis results. Additionally, deep learning was utilized to update the errors caused by material properties using the weights. This allowed for finite element analysis even when the exact physical properties of the material were unknown, ultimately improving the analysis performance.
Quantitative Analysis Method and Correction Algorithm Based on Directivity Beam Pattern for Mismatches between Sensitive Units of Acoustic Dyadic Sensors
Authors: Yang Lingmeng , Zhu Zhezheng , Chen Wangnan , Gao Chengchen , Hao Yilong , Yang Zhenchuan
Published: June 2023

Acoustic dyadic sensors (ADSs) are a new type of acoustic sensor with higher directivity than microphones and acoustic vector sensors, which has great application potential in the fields of sound source localization and noise cancellation. However, the high directivity of an ADS is seriously affected by the mismatches between its sensitive units. In this article, (1) a theoretical model of mixed mismatches was established based on the finite-difference approximation model of uniaxial acoustic particle velocity gradient and its ability to reflect the actual mismatches was proven by the comparison of theoretical and experimental directivity beam patterns of an actual ADS based on MEMS thermal particle velocity sensors. (2) Additionally, a quantitative analysis method based on directivity beam pattern was proposed to easily estimate the specific magnitude of the mismatches, which was proven to be useful for the design of ADSs to estimate the magnitudes of different mismatches of an actual ADS. (3) Moreover, a correction algorithm based on the theoretical model of mixed mismatches and quantitative analysis method was successfully demonstrated to correct several groups of simulated and measured beam patterns with mixed mismatches.
Indoor Positioning System (IPS) Using Ultra-Wide Bandwidth (UWB)—For Industrial Internet of Things (IIoT)
Authors: Che Fuhu , Ahmed Qasim Zeeshan , Lazaridis Pavlos I. , Sureephong Pradorn , Alade Temitope
Published: June 2023

The integration of the physical and digital world has become increasingly important, and location-based services have become the most sought-after application in the field of the Internet of Things (IoT). This paper delves into the current research on ultra-wideband (UWB) indoor positioning systems (IPS). It begins by examining the most common wireless communication-based technologies for IPSs followed by a detailed explanation of UWB. Then, it presents an overview of the unique characteristics of UWB technology and the challenges still faced by the IPS implementation. Finally, the paper evaluates the advantages and limitations of using machine learning algorithms for UWB IPS.
Characterizing Conformational Change of a Thermoresponsive Polymeric Nanoparticle with Raman Spectroscopy
Authors: Trabucco Luis , Heath Savannah , Shaw Jonathan , McFadden Sean , Wang Xiaodu , Ye Jing Yong
Published: June 2023

Molecular conformational changes in the collapsing and reswelling processes occurring during the phase transition at the lower critical solution temperature (LCST) of the polymer are not well understood. In this study, we characterized the conformational change of Poly(oligo(Ethylene Glycol) Methyl Ether Methacrylate)-144 (POEGMA-144) synthesized on silica nanoparticles using Raman spectroscopy and zeta potential measurements. Changes in distinct Raman peaks associated with the oligo(Ethylene Glycol) (OEG) side chains (1023, 1320, and 1499 cm−1) with respect to the methyl methacrylate (MMA) backbone (1608 cm−1) were observed and investigated under increasing and decreasing temperature profiles (34 °C to 50 °C) to evaluate the polymer collapse and reswelling around its LCST (42 °C). In contrast to the zeta potential measurements that monitor the change in surface charges as a whole during the phase transition, Raman spectroscopy provided more detailed information on vibrational modes of individual molecular moieties of the polymer in responding to the conformational change.
Environmental Engineering Applications of Electronic Nose Systems Based on MOX Gas Sensors
Authors: Khorramifar Ali , Karami Hamed , Lvova Larisa , Kolouri Alireza , Łazuka Ewa , Piłat-Rożek Magdalena , Łagód Grzegorz , Ramos Jose , Lozano Jesús , Kaveh Mohammad , Darvishi Yousef
Published: June 2023

Nowadays, the electronic nose (e-nose) has gained a huge amount of attention due to its ability to detect and differentiate mixtures of various gases and odors using a limited number of sensors. Its applications in the environmental fields include analysis of the parameters for environmental control, process control, and confirming the efficiency of the odor-control systems. The e-nose has been developed by mimicking the olfactory system of mammals. This paper investigates e-noses and their sensors for the detection of environmental contaminants. Among different types of gas chemical sensors, metal oxide semiconductor sensors (MOXs) can be used for the detection of volatile compounds in air at ppm and sub-ppm levels. In this regard, the advantages and disadvantages of MOX sensors and the solutions to solve the problems arising upon these sensors’ applications are addressed, and the research works in the field of environmental contamination monitoring are overviewed. These studies have revealed the suitability of e-noses for most of the reported applications, especially when the tools were specifically developed for that application, e.g., in the facilities of water and wastewater management systems. As a general rule, the literature review discusses the aspects related to various applications as well as the development of effective solutions. However, the main limitation in the expansion of the use of e-noses as an environmental monitoring tool is their complexity and lack of specific standards, which can be corrected through appropriate data processing methods applications.
Towards Recognition of Human Actions in Collaborative Tasks with Robots: Extending Action Recognition with Tool Recognition Methods
Authors: Büsch Lukas , Koch Julian , Schoepflin Daniel , Schulze Michelle , Schüppstuhl Thorsten
Published: June 2023

This paper presents a novel method for online tool recognition in manual assembly processes. The goal was to develop and implement a method that can be integrated with existing Human Action Recognition (HAR) methods in collaborative tasks. We examined the state-of-the-art for progress detection in manual assembly via HAR-based methods, as well as visual tool-recognition approaches. A novel online tool-recognition pipeline for handheld tools is introduced, utilizing a two-stage approach. First, a Region Of Interest (ROI) was extracted by determining the wrist position using skeletal data. Afterward, this ROI was cropped, and the tool located within this ROI was classified. This pipeline enabled several algorithms for object recognition and demonstrated the generalizability of our approach. An extensive training dataset for tool-recognition purposes is presented, which was evaluated with two image-classification approaches. An offline pipeline evaluation was performed with twelve tool classes. Additionally, various online tests were conducted covering different aspects of this vision application, such as two assembly scenarios, unknown instances of known classes, as well as challenging backgrounds. The introduced pipeline was competitive with other approaches regarding prediction accuracy, robustness, diversity, extendability/flexibility, and online capability.
Monitoring System for Operating Variables in Incubators in the Neonatology Service of a Highly Complex Hospital through the Internet of Things (IoT)
Authors: Aya-Parra Pedro Antonio , Rodriguez-Orjuela Andres Jacob , Rodriguez Torres Viviana , Cordoba Hernandez Nidia Patricia , Martinez Castellanos Natalia , Sarmiento-Rojas Jefferson
Published: June 2023

Background: Around 15 million premature babies are born annually, requiring specialized care. Incubators are vital for maintaining their body temperature, which is crucial for their well-being. Ensuring optimal conditions in incubators, including constant temperature, oxygen control, and comfort, is essential for improving the care and survival rates of these infants. Methods: To address this, an IoT-based monitoring system was developed in a hospital setting. The system comprised hardware components such as sensors and a microcontroller, along with software components including a database and a web application. The microcontroller collected data from the sensors, which was then transmitted to a broker via WiFi using the MQTT protocol. The broker validated and stored the data in the database, while the web application provided real-time access, alerts, and event recording. Results: Two certified devices were created, employing high quality components. The system was successfully implemented and tested in both the biomedical engineering laboratory and the neonatology service of the hospital. The results of the pilot test supported the concept of IoT-based technology, demonstrating satisfactory responses in temperature, humidity, and sound variables within the incubators. Conclusions: The monitoring system facilitated efficient record traceability, allowing access to data over various timeframes. It also captured event records (alerts) related to variable problems, providing information on duration, date, hour, and minutes. Overall, the system offered valuable insights and enhanced monitoring capabilities for neonatal care.
Bistable Boron-Related Defect Associated with the Acceptor Removal Process in Irradiated p-Type Silicon—Electronic Properties of Configurational Transformations
Authors: Nitescu Andrei , Besleaga Cristina , Nemnes George Alexandru , Pintilie Ioana
Published: June 2023

The acceptor removal process is the most detrimental effect encountered in irradiated boron-doped silicon. This process is caused by a radiation-induced boron-containing donor (BCD) defect with bistable properties that are reflected in the electrical measurements performed in usual ambient laboratory conditions. In this work, the electronic properties of the BCD defect in its two different configurations (A and B) and the kinetics behind transformations are determined from the variations in the capacitance-voltage characteristics in the 243–308 K temperature range. The changes in the depletion voltage are consistent with the variations in the BCD defect concentration in the A configuration, as measured with the thermally stimulated current technique. The A→B transformation takes place in non-equilibrium conditions when free carriers in excess are injected into the device. B→A reverse transformation occurs when the non-equilibrium free carriers are removed. Energy barriers of 0.36 eV and 0.94 eV are determined for the A→B and B→A configurational transformations, respectively. The determined transformation rates indicate that the defect conversions are accompanied by electron capture for the A→B conversion and by electron emission for the B→A transformation. A configuration coordinate diagram of the BCD defect transformations is proposed.
Using Deep Learning Architectures for Detection and Classification of Diabetic Retinopathy
Authors: Mohanty Cheena , Mahapatra Sakuntala , Acharya Biswaranjan , Kokkoras Fotis , Gerogiannis Vassilis C. , Karamitsos Ioannis , Kanavos Andreas
Published: June 2023

Diabetic retinopathy (DR) is a common complication of long-term diabetes, affecting the human eye and potentially leading to permanent blindness. The early detection of DR is crucial for effective treatment, as symptoms often manifest in later stages. The manual grading of retinal images is time-consuming, prone to errors, and lacks patient-friendliness. In this study, we propose two deep learning (DL) architectures, a hybrid network combining VGG16 and XGBoost Classifier, and the DenseNet 121 network, for DR detection and classification. To evaluate the two DL models, we preprocessed a collection of retinal images obtained from the APTOS 2019 Blindness Detection Kaggle Dataset. This dataset exhibits an imbalanced image class distribution, which we addressed through appropriate balancing techniques. The performance of the considered models was assessed in terms of accuracy. The results showed that the hybrid network achieved an accuracy of 79.50%, while the DenseNet 121 model achieved an accuracy of 97.30%. Furthermore, a comparative analysis with existing methods utilizing the same dataset revealed the superior performance of the DenseNet 121 network. The findings of this study demonstrate the potential of DL architectures for the early detection and classification of DR. The superior performance of the DenseNet 121 model highlights its effectiveness in this domain. The implementation of such automated methods can significantly improve the efficiency and accuracy of DR diagnosis, benefiting both healthcare providers and patients.
An Innovative Clustering Hierarchical Protocol for Data Collection from Remote Wireless Sensor Networks Based Internet of Things Applications
Authors: Shah Syed Luqman , Abbas Ziaul Haq , Abbas Ghulam , Muhammad Fazal , Hussien Aseel , Baker Thar
Published: June 2023

Recently, unmanned aerial vehicles (UAVs) have emerged as a viable solution for data collection from remote Internet of Things (IoT) applications. However, the successful implementation in this regard necessitates the development of a reliable and energy-efficient routing protocol. This paper proposes a reliable and an energy-efficient UAV-assisted clustering hierarchical (EEUCH) protocol designed for remote wireless sensor networks (WSNs) based IoT applications. The proposed EEUCH routing protocol facilitates UAVs to collect data from ground sensor nodes (SNs) that are equipped with wake-up radios (WuRs) and deployed remotely from the base station (BS) in the field of interest (FoI). During each round of the EEUCH protocol, the UAVs arrive at the predefined hovering positions at the FoI, perform clear channel assignment, and broadcast wake-up calls (WuCs) to the SNs. Upon receiving the WuCs by the SNs’ wake-up receivers, the SNs perform carrier sense multiple access/collision avoidance before sending joining requests to ensure reliability and cluster-memberships with the particular UAV whose WuC is received. The cluster-member SNs turn on their main radios (MRs) for data packet transmission. The UAV assigns time division multiple access (TDMA) slots to each of its cluster-member SNs whose joining request is received. Each SN must send the data packets in its assigned TDMA slot. When data packets are successfully received by the UAV, it sends acknowledgments to the SNs, after which the SNs turn off their MRs, completing a single round of the protocol. The proposed EEUCH routing protocol with WuR eliminates the issue of cluster overlapping, improves the overall performance, and increases network stability time by a factor of 8.7. It also improves energy efficiency by a factor of 12.55, resulting in a longer network lifespan compared to Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. Moreover, EEUCH collects 5.05 times more data from the FoI than LEACH. These results are based on simulations in which the EEUCH protocol outperformed the existing six benchmark routing protocols proposed for homogeneous, two-tier, and three-tier heterogeneous WSNs.
Risk-Aware Distributionally Robust Optimization for Mobile Edge Computation Task Offloading in the Space–Air–Ground Integrated Network
Authors: Li Zhiyuan , Chen Pinrun
Published: June 2023

As an emerging network paradigm, the space–air–ground integrated network (SAGIN) has garnered attention from academia and industry. That is because SAGIN can implement seamless global coverage and connections among electronic devices in space, air, and ground spaces. Additionally, the shortage of computing and storage resources in mobile devices greatly impacts the quality of experiences for intelligent applications. Hence, we plan to integrate SAGIN as an abundant resource pool into mobile edge computing environments (MECs). To facilitate efficient processing, we need to solve the optimal task offloading decisions. In contrast to existing MEC task offloading solutions, we have to face some new challenges, such as the fluctuation of processing capabilities for edge computing nodes, the uncertainty of transmission latency caused by heterogeneous network protocols, the uncertain amount of uploaded tasks during a period, and so on. In this paper, we first describe the task offloading decision problem in environments characterized by these new challenges. However, we cannot use standard robust optimization and stochastic optimization methods to obtain optimal results under uncertain network environments. In this paper, we propose the ‘condition value at risk-aware distributionally robust optimization’ algorithm for task offloading, denoted as RADROO, to solve the task offloading decision problem. RADROO combines the distributionally robust optimization and the condition value at risk model to achieve optimal results. We evaluated our approach in simulated SAGIN environments, considering confidence intervals, the number of mobile task offloading instances, and various parameters. We compare our proposed RADROO algorithm with state-of-the-art algorithms, such as the standard robust optimization algorithm, the stochastic optimization algorithm, the DRO algorithm, and the Brute algorithm. The experimental results show that RADROO can achieve a sub-optimal mobile task offloading decision. Overall, RADROO is more robust than others to the new challenges mentioned above in SAGIN.