bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of 3D Cooling Channels in Plastic Injection Molds by Taguchi-Integrated Principal Component Analysis (PCA)
Authors: Minh Pham Son , Dang Hung-Son , Ha Nguyen Canh
Published: February 2023

Injection molding has become an increasingly widely used method in the production of plastic parts. The injection process can be separated into five steps: mold closure, filling, packing, cooling, and product ejection. Before the melted plastic is loaded into the mold, the mold needs to be raised to a specified temperature, in order to increase the mold’s filling capacity and improve the resultant product quality. One of the easy methods used to control a mold’s temperature is to provide hot water through a cooling channel in the mold, to raise the temperature. In addition, this channel can be used for cooling the mold with cool fluid. This is simple, effective, and cost efficient, involving uncomplicated products. To improve the heating effectiveness of the hot water, a conformal cooling-channel design is considered in this paper. Through heat-transfer simulation using the CFX module in the Ansys software, an optimal cooling channel was defined according to the simulation result, using the Taguchi method integrated with principal component analysis. The comparison of traditional vs. conformal cooling channels revealed higher temperature rises in the first 100 s in both molds. During heating, conformal cooling produced higher temperatures compared with traditional cooling. Conformal cooling demonstrated better performance, with average temperature peaking at 58.78 °C and a range of 63.4 °C (max) to 54.66 °C (min). Traditional cooling resulted in an average steady-state temperature of 56.63 °C and a range of 61.74 °C (max) to 53.18 °C (min). Finally, the simulation results were verified experimentally.
Feasibility of Valorization of Post-Consumer Recycled Flexible Polypropylene by Adding Fumed Nanosilica for Its Potential Use in Food Packaging toward Sustainability
Authors: Velásquez Eliezer , López de Dicastillo Carol , Patiño Vidal Cristian , Copello Guillermo , Reyes Cristopher , Guarda Abel , Galotto María José
Published: February 2023

The food industry has a current challenge of increasing the recycling of post-consumer plastics to reduce plastic waste towards a circular economy, especially flexible polypropylene, which is highly demanded in food packaging. However, recycling post-consumer plastics is limited because service life and reprocessing degrade their physical-mechanical properties and modify the migration of components from the recycled material to the food. This research evaluated the feasibility of valorization of post-consumer recycled flexible polypropylene (PCPP) by incorporating fumed nanosilica (NS). For this purpose, the effect of concentration and type (hydrophilic and hydrophobic) of NS on the morphological, mechanical, sealing, barrier and overall migration properties of PCPP films was studied. Incorporating NS improved Young’s modulus and, more significantly, tensile strength at 0.5 wt% and 1 wt%, where a better particle dispersion was confirmed by EDS-SEM, but it diminished elongation at breakage of the films. Interestingly, NS tended to increase the seal strength of PCPP nanocomposite films more significantly at higher NS content, showing a seal failure of the adhesive peel type which is preferred for flexible packaging. NS at 1 wt% did not affect the water vapor and oxygen permeabilities of the films. Overall migration of PCPP and nanocomposites exceeded the limit value of 10 mg dm−2 allowed by European legislation at the studied concentrations of 1% and 4 wt%. Nonetheless, NS reduced the overall migration of PCPP from 17.3 to 15 mg dm−2 in all nanocomposites. In conclusion, PCPP with 1 wt% of hydrophobic NS presented an improved overall performance of the studied packaging properties.
Investigation of the Mechanical Properties of Quick-Strength Geopolymer Material Considering Preheated-to-Room Temperature Ratio of Sand, Na2SiO3-to-NaOH Ratio, and Fly Ash-to-GGBS Ratio
Authors: Bhina Mohammad Rizwan , Liu Kuang-Yen , Hu John-Eric Hsin-Yu , Tsai Chih-Ta
Published: February 2023

Geopolymer concrete is a useful alternative construction material for bridge deck systems, as it is characterized by a low carbon footprint, rapid setting, quick strength development, low cost, freeze-thaw resistance, low shrinkage, and sulphate and corrosion resistance. Heat curing enhances the mechanical properties of geopolymer materials (GPM), but it is not suitable for large structures, as it affects construction activities and increases energy consumption. Therefore, this study investigated the effect of preheated sand at varying temperatures on GPM compressive strength (Cs), the influence of Na2SiO3 (sodium silicate)-to-NaOH (sodium hydroxide—10 molar concentration), and fly ash-to-granulated blast furnace slag (GGBS) ratios on the workability, setting time, and mechanical strength properties of high-performance GPM. The results indicate that a mix design with preheated sand improved the Cs of the GPM compared to sand at room temperature (25 ± 2 °C). This was caused by the heat energy increasing the kinetics of the polymerization reaction under similar curing conditions and with a similar curing period and fly ash-to-GGBS quantity. Additionally, 110 °C was shown to be the optimal preheated sand temperature in terms of enhancing the Cs of the GPM. A Cs of 52.56 MPa was achieved after three hours of hot oven curing at a constant temperature of 50 °C. GGBS in the geopolymer paste increased the mechanical and microstructure properties of the GPM as a result of different formations of crystalline calcium silicate (C-S-H) gel. The synthesis of C-S-H and amorphous gel in the Na2SiO3 (SS) and NaOH (SH) solution increased the Cs of the GPM. We conclude that a Na2SiO3-to-NaOH ratio (SS-to-SH) of 5% was optimal in terms of enhancing the Cs of the GPM for sand preheated at 110 °C. Additionally, as the quantity of ground GGBS in the geopolymer paste increased, the thermal resistance of the GPM was significantly reduced.
Sustainable Engineered Design and Scalable Manufacturing of Upcycled Graphene Reinforced Polylactic Acid/Polyurethane Blend Composites Having Shape Memory Behavior
Authors: Cetiner Busra , Sahin Dundar Gulayse , Yusufoglu Yusuf , Saner Okan Burcu
Published: February 2023

Material design in shape memory polymers (SMPs) carries significant importance in attaining high performance and adjusting the interface between additive and host polymer matrix to increase the degree of recovery. Herein, the main challenge is to enhance the interfacial interactions to provide reversibility during deformation. The present work describes a newly designed composite structure by manufacturing a high-degree biobased and thermally induced shape memory polylactic acid (PLA)/thermoplastic polyurethane (TPU) blend incorporated with graphene nanoplatelets obtained from waste tires. In this design, blending with TPU enhances flexibility, and adding GNP provides functionality in terms of mechanical and thermal properties by enhancing circularity and sustainability approaches. The present work provides a scalable compounding approach for industrial applications of GNP at high shear rates during the melt mixing of single/blend polymer matrices. By evaluating the mechanical performance of the PLA and TPU blend composite composition at a 9:1 weight percentage, the optimum GNP amount was defined as 0.5 wt%. The flexural strength of the developed composite structure was enhanced by 24% and the thermal conductivity by 15%. In addition, a 99.8% shape fixity ratio and a 99.58% recovery ratio were attained within 4 min, resulting in the spectacular enhancement of GNP attainment. This study provides an opportunity to understand the acting mechanism of upcycled GNP in improving composite formulations and to develop a new perspective on the sustainability of PLA/TPU blend composites with an increased biobased degree and shape memory behavior.
Novel and Facile Colorimetric Detection of Reducing Sugars in Foods via In Situ Formed Gelatin-Capped Silver Nanoparticles
Authors: El-Shishtawy Reda M. , Al Angari Yasser M. , Alotaibi Maha M. , Almulaiky Yaaser Q.
Published: February 2023

The evolution of green technology for the simple and ecological formation of silver nanoparticles (AgNPs) inspired the present work for simple and efficient detection of reducing sugars (RS) in foods. The proposed method relies on gelatin as the capping and stabilizing agent and the analyte (RS) as the reducing agent. This work may attract significant attention, especially in the industry, for testing the sugar content using gelatin-capped silver nanoparticles as it not only detects the sugar in food, but also determines the content (%), which could be an alternative technique to the conventionally used DNS colorimetric method. For this purpose, a certain amount of maltose was mixed with a gelatin-silver nitrate. Different conditions that may affect the color changes at 434 nm owing to the in situ formed AgNPs, such as gelatin-silver nitrate ratio, PH, time, and temperature, have been investigated. The 1:3 mg/mg ratio of gelatin-silver nitrate dissolved in 10 mL distilled water was most effective in color formation. The development of AgNPs color increases within 8–10 min at PH 8.5 as the selected optimum value and at the optimum temperature of 90 °C for the evolution of the gelatin-silver reagent’s redox reaction. The gelatin-silver reagent showed a fast response (less than 10 min) with a detection limit for maltose at 46.67 µM. In addition, the selectivity of maltose was checked in the presence of starch and after its hydrolysis with α-amylase. Compared with the conventionally used dinitrosalicylic acid (DNS) colorimetric method, the proposed method could be applied to commercial fresh apple juice, watermelon, and honey to prove its viability for detecting RS in fruits; the total reducing sugar content was 287, 165, and 751 mg/g, respectively.
Synthesis of Furan-Based Diamine and Its Application in the Preparation of Bio-Based Polyimide
Authors: Zhang Yao , Chen Lei , He Yima , Luo Weiyu , Li Kaixin , Min Yonggang
Published: February 2023

Furan-based compounds are a new class of compounds characteristic of wide abundance, feasible availability, and environmental friendliness. Presently, polyimide (PI) is the best membrane insulation material in the world, which is widely used in the fields of national defense, liquid crystals, lasers, and so on. At present, most polyimides are synthesized using petroleum-based monomers bearing benzene rings, while furan-based compounds bearing furan rings are rarely used as monomers. The production of petroleum-based monomers is always associated with many environmental issues, and their substitution with furan-based compounds seems a solution to addressing these issues. In this paper, t-butoxycarbonylglycine (BOC-glycine) and 2,5-furandimethanol, bearing furan rings, were employed to synthesize BOC-glycine 2,5-furandimethyl ester, which was further applied for the synthesis of furan-based diamine. This diamine is generally used to synthesize bio-based PI. Their structures and properties were thoroughly characterized. The characterization results showed that BOC-glycine could be effectively obtained using different posttreatment methods. And BOC-glycine 2,5-furandimethyl ester could be effectively obtained by optimizing the accelerating agent of 1,3-dicyclohexylcarbodiimide(DCC) with either 1.25 mol/L or 1.875 mol/L as the optimum value. The PIs originated from furan-based compounds were synthesized and their thermal stability and surface morphology were further characterized. Although the obtained membrane was slightly brittle (mostly due to the less rigidity of furan ring as compared with benzene ring), the excellent thermal stability and smooth surface endow it a potential substitution for petroleum-based polymers. And the current research is also expected to shed some insight into the design and the fabrication of eco-friendly polymers.
Vibration Isolation Properties of Novel Spacer Fabric with Silicone Inlay
Authors: Yu Annie , Sukigara Sachiko , Masuda Arata
Published: February 2023

Spacer fabrics are good for impact force absorption and have the potential for vibration isolation. Inlay knitting of additional material to the spacer fabrics can give reinforcement to the structure. This study aims to investigate the vibration isolation properties of three-layer sandwich fabrics with silicone inlay. The effect of the presence of the inlay, inlay patterns and materials on the fabric geometry, vibration transmissibility and compression behaviour were evaluated. The results showed that the silicone inlay increases the unevenness of the fabric surface. The fabric using polyamide monofilament as the spacer yarn in the middle layer creates more internal resonance than that using polyester monofilament. Silicone hollow tubes inlay increases the magnitude of damping vibration isolation, whereas inlaid silicone foam tubes have the opposite effect. Spacer fabric with silicone hollow tubes inlaid by tuck stitches has not only high compression stiffness but also becomes dynamic, showing several resonance frequencies within the tested frequency range. The findings show the possibility of the silicone inlaid spacer fabric and provide a reference for developing vibration isolation materials with knitted structure and textiles materials.
On God and the Beginning of the Universe: An Evaluation of Recent Discussions
Authors: Loke Andrew Ter Ern
Published: February 2023

Philosophical analysis is of vital importance for addressing the controversies in science and theology. This article evaluates the analyses concerning God and the beginning of the universe offered by a number of philosophers. It is shown that, while Linford is correct in that establishing that physical reality has a finite past is not sufficient for establishing that physical reality had a beginning, the objections which Linford, Schmid, Oberle, and Wielenberg have offered against the Cosmological Argument for the existence of God can be rebutted. The examination of the objections and rebuttals demonstrates how a more careful philosophical analyses of the issues concerning the argument against infinite causal regress, personal identity, timelessness, the definition and reducibility of time, and the causal principle can contribute to the interaction between science and theology.
Between the Tibetan Plateau and Eastern China—Religious Tourism, Lay Practice and Ritual Economy during the Pandemic
Authors: Shmushko Kai
Published: February 2023

This article presents various institutional responses of Buddhist groups and leaders to COVID-19, adding a focus on how Tibetan Buddhist practitioners in China have responded to the pandemic. In particular, it examines the predicament of practitioners of Tibetan Buddhism. The article focuses on the material characteristics of Tibetan Buddhism and how they were manifested among Han Chinese urbanites during the pandemic through (1) a teleological inquiry, which looks into the concept of merit (sk: puñña, ch: gongde) 功德, and (2) an organizational inquiry, which explores the modalities in which Han Chinese groups practice Tibetan Buddhism in the socio-political sphere of the Chinese state. Within this inquiry, the article deals with a Buddhist community based in Shanghai and an individual account of pilgrimage in Tibet. Based on these two case studies and their contextualization, the article aims to assess how the COVID-19 crisis has affected the practices, modalities and religious technologies of Tibetan Buddhism practiced by Han Chinese. The article argues for a degree of resilience of lay practice in Tibetan Buddhism; it stresses that while some aspects of the practice called for accommodations and change, the particularities of the practice have pre-existing conditions (such as state regulation on religion and the physical distance of their religious authority) which could accommodate the practical, sociological and psychological implications of the COVID-19 pandemic.
“God, Guns, and Guts”: Christian Nationalism from a Psychoanalytic Perspective
Authors: Cooper-White Pamela
Published: February 2023

This article explores the motivations behind adherents to Christian nationalism using several inter-related psychoanalytic theoretical lenses. Following a description of Christian nationalist beliefs, four conscious motivations for joining will be outlined first, including recruitment tactics/evangelization that fulfill the need for belonging and a sense of sacred purpose, the fear of loss of white social status, fear of loss of patriarchal authority and hierarchy, and the allure of conspiracy theories such as QAnon for conservative Christians. This will be followed by a more in-depth discussion of unconscious dynamics that can fuel individuals’ adoption of a Christian-nationalist belief system, including group dynamics and Freud’s insights into the power of a charismatic leader, the allure of guns reflecting deeper unconscious fears of emasculation, paranoid splitting and the role of trauma, and, finally, the ways in which this segment of American Christianity may be unconsciously carrying disavowed and split-off aggression towards other Christians—and how better integration might be achieved through nonviolent resistance to injustice, and positive political engagement.
Spectrum of Response Styles in a Religious-Orthodox Community to Civilian Disasters: The Responses of the Haredi Community to the Meron Crowd Crush (2021) as a Case Study
Authors: Gado Tehila , Fishof David
Published: February 2023

Over the past few decades the Haredi community has been expanding and it includes a diversity of groups characterized by wide margins, therefore it may be considered an imagined community. On Lag Ba’Omer 2021, 45 people died, and over 150 were injured in the Meron Crowd Crush, most of them from the diverse Haredi community in Israel. Coping with disasters in a religious community includes a religious-faith level, and a social level. In this study, we will examine the response styles to a disaster in the Haredi community, as a case study of religious communities coping with a civilian disaster. This study will assist in understanding the community’s narrative, and the place of the community in coping with a disaster. The study uses the qualitative-constructivist method and applies a categorical analysis of 1146 verbal responses to an internet survey that was conducted subsequent to the disaster. We propose a theoretical-categorical model that divides the responses into five pairs of categories: Emotional, Religious, Spiritual-Transcendental, Social, and Civil responses, each pair divided into past and future. Emotional responses: expressing grief and mourning (past), or paralysis, anxiety, and instability, (future); Religious responses: search for a religious reason (past), or a call for religious strengthening (future); Spiritual-Transcendent responses: dealing with questions of faith (past), or viewing the disaster as a transcendent message, and seeking spiritual comfort (future); Social-Spiritual responses: attributing the disaster to collective punishment due to ‘corruption’ (past), or recommendations for ‘correction’ of the social world (future); Civil responses: including searching for deficiencies, blaming entities (past), or suggestions for improvements and correction of deficiencies (future). We discussed a spectrum of response styles, while distinguishing between responses that are concerned with finding a reason or explanation for the disaster (past), and those who wish to draw a conclusion (future). Furthermore, social injustices are seen as religious offenses that led to the disaster. That is, it is a religious soul-searching that deals, less with traditional offenses and more with social injustices. We also discussed the volume of the different responses: In the emotional reactions and civil reactions, the Past Category is larger than the Future, whereas in the religious and spiritual responses, the Future categories are larger. This finding may symbolize a tendency to channel the pain in a positive way to a practical and active direction. Religious actions provide a sense of agency and self-efficacy. At last, we noticed that the disaster led to the strengthening of the community and sense of community, despite its size and diversity; as well, we suggested that the findings regarding religious-orthodox communities and their coping with disasters can be inferred.
Modeling the Impact of Fees and Circular Economy Options on the Financial Sustainability of the Solid Waste Management System in Jordan
Authors: Abu-Qdais Hani A. , Shatnawi Nawras , Al-Shahrabi Rami
Published: February 2023

Municipal solid waste services in Jordan are being provided by municipalities, where 90% of the generated solid waste finds its way to the landfills and dump sites. All Jordanian municipalities are suffering from low cost recovery where it reaches 50% in its best case. Realizing these facts, recently, the Jordanian government has embarked on an ambitious package of regulations and policies to promote the adoption of circular economy options. The National Solid Waste Management Strategy (NSWMS) of Jordan has called for rationalization, gradual increase of the service fees and adoption of circular economy options through recycling and composting. To assess the impacts of the proposed policies by the NSWMS on the financial sustainability, a system dynamic modeling (SDM) was carried out for the two largest municipalities in the country, namely Greater Amman Municipality (GAM) and Greater Irbid Municipality (GIM). The share of solid waste management cost from the total municipal budget in GAM and GIM is 13.3% and 24%, respectively. On the other hand, the cost per ton of solid waste management in GAM is USD 85 and in GIM it is USD 50. Medium-term and long-term scenarios were considered in the SDM analysis. By considering the year 2016 as a baseline year, the simulation revealed that during the midterm period (2022–2026), the cost recovery will be increased from 54% to 82.5% in GAM, while in GIM it will be raised from 45% to 70%. Moreover, during the long-term period (2027–2034) as a result of adopting circular economy options by recycling and composting, both GAM and GIM will achieve full cost recovery of the solid waste services, in 2028 and 2029, respectively. Furthermore, diverting the solid waste from the landfill will lead to climate change mitigation, where about 652,275 tons of CO2eq. and greenhouse gases will be avoided. It is recommended that municipalities in Jordan should consider a more efficient solid waste collection mechanism rather than through electricity bills. Further research is needed to assess the impact of other circular economy options such as waste to energy and extended producer responsibility (EPR).
YOLOLens: A Deep Learning Model Based on Super-Resolution to Enhance the Crater Detection of the Planetary Surfaces
Authors: La Grassa Riccardo , Cremonese Gabriele , Gallo Ignazio , Re Cristina , Martellato Elena
Published: February 2023

The impact crater detection offers a great scientific contribution in analyzing the geological processes, morphologies and physical properties of the celestial bodies and plays a crucial role in potential future landing sites. The huge amount of craters requires automated detection algorithms, and considering the low spatial resolution provided by the satellite jointly with, the solar illuminance/incidence variety, these methods lack their performance in the recognition tasks. Furthermore, small craters are harder to recognize also by human experts and the need to have a sophisticated detection algorithm becomes mandatory. To address these problems, we propose a deep learning architecture refers as “YOLOLens5x”, for impact crater detection based on super-resolution in a unique end-to-end design. We introduce the entire workflow useful to link the Robbins Lunar catalogue with the tiles orthoprojected from the Lunar mosaic LROC mission in order to train our proposed model as a supervised paradigm and, the various optimization due to provide a clear dataset in the training step. We prove by experimental results a boost in terms of precision and recall than the other state-of-the-art crater detection models, reporting the lowest error estimated craters diameter using the same scale factor given by LROC WAC Camera. To simulate the camera satellite at the lowest spatial resolution, we carried out experiments at different scale factors (200 m/px, 400 m/px) by interpolating the source image of 100 m/px, bringing to light remarkable results across all metrics under consideration compared with the baseline used.
The Ecological Evolution Analysis of Heritage Sites Based on The Remote Sensing Ecological Index—A Case Study of Kalajun–Kuerdening World Natural Heritage Site
Authors: He Baoshi , Han Fang , Han Jiali , Ren Qingliu , Li Ying
Published: February 2023

As very fragile natural ecological areas, the spatiotemporal ecological environment (EE) analysis of World Natural Heritage Sites (WNHSs) is particularly important for their conservation and sustainable development. Timely, objective and quantitative evaluation of the spatiotemporal EE change characteristics of WNHSs is of great significance for ecological, environmental protection and government policy formulation. This study quantitatively evaluates the spatiotemporal distribution characteristics of the EE of the Kalajun–Kuerdening WNHS by selecting the Remote Sensing Ecological Environment Index (RSEI) for 2006, 2011, 2016 and 2021. We studied the spatiotemporal differences of the EE in buffer zones and nominated sites in the heritage sites and their change patterns and trends. The EE changes and land use changes from 2006–2011, 2011–2016 and 2016–2021 were overlaid and analyzed to explore the relationship between EE evolution and land use changes in the heritage site. The results show that (1) the heritage site was in a state of ecological change equilibrium from 2006 to 2011, and a form of slight decline in EE quality from 2011 to 2016 under the influence of natural factors, but it maintained a stable state with a small degree of fluctuation, and a state of ecological change recovery from 2016 to 2021. The areas with better EE grades were located in the northwest region (Kalajun) and northeast region (Kuerdening) of the heritage site. (2) The EE grade change in the heritage site shows the characteristics of neighborhood change without a large number of leap changes. (3) From 2006 to 2021, the EE quality in the nominated site was better than that of the buffer zone, but from 2016 onward, the difference between the two gradually decreased until 2021. The average EE quality was basically the same until 2021, but, spatially, the EE quality of most areas in the buffer zone was better than that in the nominated area. (4) The types of land use transformation that caused EE enhancement in the heritage sites were barren–grassland, snow/ice–barren and barren–snow/ice, while the types of land use transformation that caused EE quality reduction were grassland–barren and barren–snow/ice. The results of this study help improve the knowledge of the EE background of the WNHS and its evolutionary process and provide scientific guidance for ecologically related decision making and management of global natural heritage sites. The change in snow and ice cover is an essential factor in the shift of the EE of the Kalajun–Kuerdening World Natural Heritage Site.
Night-Time Detection of Subpixel Emitters with VIIRS Mid-Wave Infrared Bands M12–M13
Authors: Zhizhin Mikhail , Elvidge Christopher , Poyda Alexey
Published: February 2023

In this paper, we present a new approach to subpixel infrared (IR) emitter detection in VIIRS mid-wave (MWIR) infrared bands M12–M13 at night, based on the presence of a tightly clustered background diagonal present in full granule scattergrams of M12 versus M13 radiances. This diagonal is found universally in night-time VIIRS data collected worldwide. The diagonal feature is absent during the day due to solar reflectance. The existence of the diagonal is attributed to close spacing in the bandpass centers of the VIIRS’ two MWIR bands. Apparently, the M12 and M13 emissivities are highly correlated to background objects, such clouds, ocean and land surfaces. The VIIRS Nightfire (VNF) algorithm detects pixels containing IR emitters based on their departure from the background diagonal. This paper outlines the method and compares VNF results with those from MODIS and VIIRS hotspot detection.
A Localization Algorithm Based on Global Descriptor and Dynamic Range Search
Authors: Chen Yongzhe , Wang Gang , Zhou Wei , Zhang Tongzhou , Zhang Hao
Published: February 2023

The map-based localization method is considered an effective supplement to the localization under the GNSS-denied environment. However, since the map is constituted by the dispersed keyframes, it sometimes happens that the initial position of the unmanned ground vehicle (UGV) lies between the map keyframes or is not on the mapping trajectory. In both cases, it will be impossible to precisely estimate the pose of the vehicle directly via the relationship between the current frame and the map keyframes, leading to localization failure. In this regard, we propose a localization algorithm based on the global descriptor and dynamic range search (LA-GDADRS). In specific, we first design a global descriptor shift and rotation invariant image (SRI), which improves the rotation invariance and shift invariance by the methods of coordinates removal and de-centralization. Secondly, we design a global localization algorithm for shift and rotation invariant branch-and-bound scan matching (SRI-BBS). It first leverages SRI to obtain an approximate priori position of the unmanned vehicle and then utilizes the similarity between the current frame SRI and the map keyframes SRI to select a dynamic search range around the priori position. Within the search range, we leverage the branch-and-bound scanning matching algorithm to search for a more precise pose. It solves the problem that global localization tends to fail when the priori position is imprecise. Moreover, we introduce a tightly coupled factor graph model and a HD map engine to achieve real-time position tracking and lane-level localization, respectively. Finally, we complete extensive ablation experiments and comparative experiments to validate our methods on the benchmark dataset (KITTI) and the real application scenarios at the campus. Extensive experimental results demonstrate that our algorithm achieves the performance of mainstream localization algorithms.
Analysis of Acoustic–Magnetic Fields Induced by Underwater Pressure Wave in a Finite-Depth Ocean
Authors: Zhou Yuanguo , Huang Peng , Yang Guoqing , Liang Shangqing , Ren Qiang , Tian Shiwei
Published: February 2023

As underwater disturbances (natural or artificial) occur in the ocean, moving seawater crossing the geomagnetic fields will produce weak circular currents. These currents can induce measurable magnetic fields, which might be useful for monitoring ocean internal waves using aeromagnetic survey. In this research, a spectral-element method (SEM) based on Gauss–Lobatto–Legendre (GLL) polynomials is presented to characterize the magnetic field induced by the underwater pressure waves. A concise mathematical model is established through combining the acoustic wave equations and Maxwell’s equations. Specifically, the acoustic–magnetic coupling simulation adopts the nodal-based SEM for acoustic analysis and edge-based SEM for electromagnetic analysis. The proposed SEM has spectral accuracy, as the error exponentially decreases with the order of the basis functions. Additionally, by adopting an independent modeling and mesh scheme in two solvers, respectively, the waste of computing resources is avoided. The experimental analysis demonstrates that the induced magnetic fields mechanically propagate with the acoustic wave, producing the pseudo-radiation phenomenon. The signals of these magnetic fields may extend for tens of kilometers and exist for hours under certain circumstances, which provide a theoretical basis for underwater target identification via high-sensitivity atomic magnetometer.
Visualization of Environmental Sensing Data in the Lake-Oriented Digital Twin World: Poyang Lake as an Example
Authors: Chen Hao , Fang Chaoyang , Xiao Xin
Published: February 2023

Access to real-time environmental sensing data is key to representing real-time environmental changes in the digital twin of lakes. The visualization of environmental sensing data is an important part of establishing a digital twin of lakes. In the past, environmental sensing data display methods were either charts or two-dimensional map-based visualization methods. Breaking through the traditional visualization methods of environmental sensing data and realizing a multi-dimensional and multi-view display of environmental sensing data in a digital twin of lakes is something that this particular paper tries to resolve. This study proposes a visualization framework to integrate, manage, analyze, and visualize the environmental sensing data in the digital twin of lakes. In addition, this study also seeks to realize the coupling expression of geospatial data and long-term monitoring sequence data. Different visualization methods are used to realize the visualization of environmental sensing data in the digital twin of lakes. Using vector and scalar visualization methods to display ambient wireless sensor monitoring data in a digital twin of lakes provides researchers with richer visualization methods and means for deeper analysis. Using video fusion technology to display environmental sensing video surveillance data strengthens the integration of the virtual environment and real space and saves time for position identification using video surveillance. These findings may also help realize the integration and management of real-time environmental sensing data in a digital twin of lakes. The visualization framework uses various visualization methods to express the monitoring data of environmental wireless sensors and increases the means of visualizing environmental sensing data in the world of a lake digital twin. This visualization framework is also a general approach that can be applied to all similar lakes, or other geographical scenarios where environmental sensing devices are deployed. The establishment of a digital twin of Poyang Lake has certain practical significance for improving the digital management level of Poyang Lake and monitoring its ecological changes. Poyang Lake is used as an example to verify the proposed framework and method, which shows that the framework can be applied to the construction of a lake-oriented digital twin.
Impact of SAR Azimuth Ambiguities on Doppler Velocity Estimation Performance: Modeling and Analysis
Authors: Sun Kai , Diao Lijie , Zhao Yawei , Zhao Wenjia , Xu Yongsheng , Chong Jinsong
Published: February 2023

Doppler Centroid Analysis (DCA) technique is one of the major techniques that do permit a direct retrieval of ocean surface velocity from synthetic aperture radar (SAR) data. However, azimuth ambiguities in the SAR images severely restrict the capability of DCA technique to obtain accurate ocean surface Doppler velocities. Therefore, it is necessary to investigate how the azimuth ambiguities impact the Doppler velocity estimation performance and to evaluate how significant the impact is. In this paper, a model for ocean surface Doppler velocity estimation affected by azimuth ambiguities is developed resorting to jointly circular Gaussian processes, and its statistic is derived. The impact of azimuth ambiguities on Doppler velocity estimation performance in terms of Doppler centroid estimation bias and the standard deviation of Doppler centroid estimates is analyzed. The theoretical results are validated through simulation and Doppler velocities retrieved from Chinese Gaofen-3 (GF-3) SAR Doppler centroid estimates affected by azimuth ambiguities. This study will help researchers better understand the impact of azimuth ambiguities on Doppler velocity estimation, and will provide a theoretical reference for subsequent research on how to reduce the impact of azimuth ambiguities more effectively.
Intelligent Fusion Structure for Wi-Fi/BLE/QR/MEMS Sensor-Based Indoor Localization
Authors: Yu Yue , Zhang Yi , Chen Liang , Chen Ruizhi
Published: February 2023

Due to the complexity of urban environments, localizing pedestrians indoors using mobile terminals is an urgent task in many emerging areas. Multi-source fusion-based localization is considered to be an effective way to provide location-based services in large-scale indoor areas. This paper presents an intelligent 3D indoor localization framework that uses the integration of Wi-Fi, Bluetooth Low Energy (BLE), quick response (QR) code, and micro-electro-mechanical system sensors (the 3D-WBQM framework). An enhanced inertial odometry was developed for accurate pedestrian localization and trajectory optimization in indoor spaces containing magnetic interference and external acceleration, and Wi-Fi fine time Measurement stations, BLE nodes, and QR codes were applied for landmark detection to provide an absolute reference for trajectory optimization and crowdsourced navigation database construction. In addition, the robust unscented Kalman filter (RUKF) was applied as a generic integrated model to combine the estimated location results from inertial odometry, BLE, QR, Wi-Fi FTM, and the crowdsourced Wi-Fi fingerprinting for large-scale indoor positioning. The experimental results indicated that the proposed 3D-WBQM framework was verified to realize autonomous and accurate positioning performance in large-scale indoor areas using different location sources, and meter-level positioning accuracy can be acquired in Wi-Fi FTM supported areas.
Performance Analysis of Real-Time GPS/Galileo Precise Point Positioning Integrated with Inertial Navigation System
Authors: Zhao Lei , Blunt Paul , Yang Lei , Ince Sean
Published: February 2023

The integration of global navigation satellite system (GNSS) precise point positioning (PPP) and inertial navigation system (INS) is widely used in navigation for its robustness and resilience, especially in case of GNSS signal blockage. With GNSS modernization, a variety of PPP models have been developed and studied, which has also led to various PPP/INS integration methods. In this study, we investigated the performance of a real-time GPS/Galileo zero-difference ionosphere-free (IF) PPP/INS integration with the application of uncombined bias products. This uncombined bias correction was independent of PPP modeling on the user side and also enabled carrier phase ambiguity resolution (AR). CNES (Centre National d’Etudes Spatiales) real-time orbit, clock, and uncombined bias products were used. Six positioning modes were evaluated, including PPP, PPP/INS loosely coupled integration (LCI), PPP/INS tightly coupled integration (TCI), and three of these with uncombined bias correction through a train positioning test in an open sky environment and two van positioning tests at a complex road and city center. All of the tests used a tactical-grade inertial measurement unit (IMU). In the train test, we found that ambiguity-float PPP had almost identical performance with LCI and TCI, which reached an accuracy of 8.5, 5.7, and 4.9 cm in the north (N), east (E) and up (U) direction, respectively. After AR, significant improvements on the east error component were achieved, which were 47%, 40%, and 38% for PPP-AR, PPP-AR/INS LCI, and PPP-AR/INS TCI, respectively. In the van tests, frequent signal interruptions due to bridges, vegetation, and city canyons make the IF AR difficult. TCI achieved the highest accuracies, which were 32, 29, and 41 cm for the N/E/U component, respectively, and also effectively eliminated the solution re-convergence in PPP.
Ultra-High-Speed Accelerator Architecture for Convolutional Neural Network Based on Processing-in-Memory Using Resistive Random Access Memory
Authors: Wang Hongzhe , Wang Junjie , Hu Hao , Li Guo , Hu Shaogang , Yu Qi , Liu Zhen , Chen Tupei , Zhou Shijie , Liu Yang
Published: February 2023

Processing-in-Memory (PIM) based on Resistive Random Access Memory (RRAM) is an emerging acceleration architecture for artificial neural networks. This paper proposes an RRAM PIM accelerator architecture that does not use Analog-to-Digital Converters (ADCs) and Digital-to-Analog Converters (DACs). Additionally, no additional memory usage is required to avoid the need for a large amount of data transportation in convolution computation. Partial quantization is introduced to reduce the accuracy loss. The proposed architecture can substantially reduce the overall power consumption and accelerate computation. The simulation results show that the image recognition rate for the Convolutional Neural Network (CNN) algorithm can reach 284 frames per second at 50 MHz using this architecture. The accuracy of the partial quantization remains almost unchanged compared to the algorithm without quantization.
Survey on Intrusion Detection Systems Based on Machine Learning Techniques for the Protection of Critical Infrastructure
Authors: Pinto Andrea , Herrera Luis-Carlos , Donoso Yezid , Gutierrez Jairo A.
Published: February 2023

Industrial control systems (ICSs), supervisory control and data acquisition (SCADA) systems, and distributed control systems (DCSs) are fundamental components of critical infrastructure (CI). CI supports the operation of transportation and health systems, electric and thermal plants, and water treatment facilities, among others. These infrastructures are not insulated anymore, and their connection to fourth industrial revolution technologies has expanded the attack surface. Thus, their protection has become a priority for national security. Cyber-attacks have become more sophisticated and criminals are able to surpass conventional security systems; therefore, attack detection has become a challenging area. Defensive technologies such as intrusion detection systems (IDSs) are a fundamental part of security systems to protect CI. IDSs have incorporated machine learning (ML) techniques that can deal with broader kinds of threats. Nevertheless, the detection of zero-day attacks and having technological resources to implement purposed solutions in the real world are concerns for CI operators. This survey aims to provide a compilation of the state of the art of IDSs that have used ML algorithms to protect CI. It also analyzes the security dataset used to train ML models. Finally, it presents some of the most relevant pieces of research on these topics that have been developed in the last five years.
Arbitrary-Shaped Text Detection with B-Spline Curve Network
Authors: You Yuwei , Lei Yuxin , Zhang Zixu , Tong Minglei
Published: February 2023

Text regions in natural scenes have complex and variable shapes. Directly using contour coordinates to describe text regions will make the modeling inadequate and lead to low accuracy of text detection. To address the problem of irregular text regions in natural scenes, we propose an arbitrary-shaped text detection model based on Deformable DETR called BSNet. The model differs from the traditional method of directly predicting contour points by using B-Spline curve to make the text contour more accurate and reduces the number of predicted parameters simultaneously. The proposed model eliminates manually designed components and dramatically simplifies the design. The proposed model achieves F-measure of 86.8% and 87.6% on CTW1500 and Total-Text, demonstrating the model’s effectiveness.
Human Recognition Using Deep Neural Networks and Spatial Patterns of SSVEP Signals
Authors: Oikonomou Vangelis P.
Published: February 2023

Brain biometrics have received increasing attention from the scientific community due to their unique properties compared to traditional biometric methods. Many studies have shown that EEG features are distinct across individuals. In this study, we propose a novel approach by considering spatial patterns of the brain’s responses due to visual stimulation at specific frequencies. More specifically, we propose, for the identification of the individuals, to combine common spatial patterns with specialized deep-learning neural networks. The adoption of common spatial patterns gives us the ability to design personalized spatial filters. In addition, with the help of deep neural networks, the spatial patterns are mapped into new (deep) representations where the discrimination between individuals is performed with a high correct recognition rate. We conducted a comprehensive comparison between the performance of the proposed method and several classical methods on two steady-state visual evoked potential datasets consisting of thirty-five and eleven subjects, respectively. Furthermore, our analysis includes a large number of flickering frequencies in the steady-state visual evoked potential experiment. Experiments on these two steady-state visual evoked potential datasets showed the usefulness of our approach in terms of person identification and usability. The proposed method achieved an averaged correct recognition rate of 99% over a large number of frequencies for the visual stimulus.
Optimization Model and Solution Algorithm for Rural Customized Bus Route Operation under Multiple Constraints
Authors: Zhang Bing , Zhong Zhishan , Zhou Xun , Qu Yongqiang , Li Fangwei
Published: February 2023

In order to improve the operational efficiency of public transportation systems in rural areas, we investigated the demand-responsive rural customized bus vehicle route optimization problem. First, a two-stage planning model describing the problem in the reservation phase and real-time phase was constructed with the objectives of minimizing the operating cost of the operator and the travel time cost of the passenger, and the passenger time window, vehicle characteristics, rated passenger capacity and the running time of the route were considered in the constraints. Second, a hybrid algorithm solution model combining bat algorithm and adaptive particle swarm algorithm was designed to obtain a more optimal solution. Finally, the effectiveness of the hybrid algorithm on the optimization model was verified by using the actual road network in some townships of Jing’an County, Jiangxi Province, China, and the obtained objective function value was reduced by 5.5%. The results show that the optimization model and hybrid algorithm designed in this paper can be used to provide theoretical references for opening demand-responsive customized bus route operation schemes in rural areas.
Adoption of the PICRAT Model to Guide the Integration of Innovative Technologies in the Teaching of a Linguistics Course
Authors: Wang Lixun
Published: February 2023

Due to the pandemic, more and more innovative technologies have been integrated into language education for blended and online learning. However, teachers often feel overwhelmed by various available technologies, and they need a framework that will guide them to integrate innovative technologies into their teaching effectively. This paper reports on the adoption of the PICRAT model that guided the integration of innovative technologies in the teaching of an undergraduate level linguistics course. The PICRAT model is a pedagogical framework for technology integration in education: students’ relationship with technology can be passive, interactive, and creative (PIC), and teachers’ use of technologies may replace, amplify, and transform (RAT) traditional practices. Guided by the PICRAT model, a wide range of innovative e-learning tools/resources were adopted in the course, such as VR applications, Flipgrid video sharing, EdPuzzle interactive video lectures, and Wikibook project. A total of 105 students participated in the course, and a questionnaire survey and follow-up interviews were conducted to collect students’ feedback regarding the adoption of the PICRAT model in the course. The findings suggest that by systematically adopting various technologies to replace, amplify, and transform traditional practices, the teacher managed to turn students from passive learners into interactive and creative learners, leading to enhanced student performances and satisfactory learning outcomes.