bluuebunny/crossref_metadata_2025 huggingface dataset:
Development Trend in Composition Optimization, Microstructure Manipulation, and Strengthening Methods of Die Steels under Lightweight and Integrated Die Casting
Authors: Bao Ze-Ju , Yang Hong-Yu , Dong Bai-Xin , Chang Fang , Li Chuan-De , Jiang Ying , Chen Liang-Yu , Shu Shi-Li , Jiang Qi-Chuan , Qiu Feng
Published: September 2023

In the general environment of lightweight automobiles, the integrated die-casting technology proposed by Tesla has become the general mode to better achieve weight reduction in automobiles. The die-casting mold required by integrated die-casting technology has the characteristics of large scale and complexity. Hence, higher requirements are put forward for the comprehensive performance of the die steel. Despite the stagnation in the progress of conventional strengthening methods, enhancing the performance of die steel has become increasingly challenging. Indeed, it necessitates exploring novel die steel and optimizing heat treatment and reinforcement technologies. This article summarizes and analyzes the development status of die steel and corresponding heat treatment and microstructure manipulation as well as strengthening methods and elaborates on an excellent nano-strengthening technology. Furthermore, this review will aid researchers in establishing a comprehensive understanding of the development status of die steel and the processes utilized for its strengthening. It will also assist them in developing die steel with improved comprehensive performance to meet the high demand for mold steel in the integrated die-casting technology of the new era.
A 3D-Printed Ceramics Innovative Firing Technique: A Numerical and Experimental Study
Authors: Santos Tiago , Ramani Melinda , Devesa Susana , Batista Catarina , Franco Margarida , Duarte Isabel , Costa Luís , Ferreira Nelson , Alves Nuno , Pascoal-Faria Paula
Published: September 2023

Additive manufacturing (AM), also known as three-dimensional (3D) printing, allows the fabrication of complex parts, which are impossible or very expensive to produce using traditional processes. That is the case for dinnerware and artworks (stoneware, porcelain and clay-based products). After the piece is formed, the greenware is fired at high temperatures so that these pieces gain its mechanical strength and aesthetics. The conventional (gas or resistive heating elements) firing usually requires long heating cycles, presently requiring around 10 h to reach temperatures as high as 1200 °C. Searching for faster processes, 3D-printed stoneware were fired using microwave (MW) radiation. The pieces were fired within 10% of the conventional processing time. The temperature were controlled using a pyrometer and monitored using Process Temperature Control Rings (PTCRs). An error of 1.25% was calculated between the PTCR (1207 ± 15 °C) and the pyrometer (1200 °C). Microwave-fast-fired pieces show similar mechanical strength to the references and to the electrically fast-fired pieces (41, 46 and 34 (N/mm2), respectively), presenting aesthetic features closer to the reference. Total porosities of ~4%, ~5% and ~9% were determined for microwave, electrically fast-fired and reference samples. Numerical studies have shown to be essential to better understand and improve the firing process using microwave radiation. In summary, microwave heating can be employed as an alternative to stoneware conventional firing methods, not compromising the quality and features of the processed pieces, and with gains in the heating time.
Wood-Poly(furfuryl Alcohol) Prepreg: A Novel, Ecofriendly Laminate Composite
Authors: Acosta Andrey Pereira , Esteves Bruno , Cruz Joziel Aparecido da , Aramburu Arthur Behenck , Kairytė Agnė , Członka Sylwia , Ramos Dionatan Orestes , Goularte Matheus de Paula , Delucis Rafael de Avila , Gatto Darci Alberto , Amico Sandro Campos
Published: September 2023

Prepregs are commonly fabricated with non-renewable petroleum-based materials. To reduce the impact of the manufacturing of these materials and to produce more sustainable prepregs, this research aims to manufacture poly(furfuryl alcohol)/wood veneer prepregs and their posterior molding in laminate composites. For this purpose, the vacuum infusion process was used to impregnate the wood veneers, and compression molding was applied to manufacture three- and four-layer laminate composites. Scanning electronic microscopy was used to evaluate the impregnation. the laminate manufacturing and differential scanning calorimetry were used to predict the shelf-life of the prepregs, Fourier-transform infrared was used to evaluate the induced hydrolysis resistance, and thermogravimetric analysis was used to determine the thermal degradation of the laminates. Moreover, water uptake and flexural, compressive, and tensile properties were evaluated. The kinetic models were effective and showed a shelf life for the laminates of approximately 30 days in storage at −7 °C, which is an interesting result for laminates with lignocellulosic materials. FTIR proved the laminates’ excellent resistance to hydrolysis. The water absorption, thermal stability, and mechanical properties did not differ as the amount of wood veneer increased, but these results were up to ~40% higher compared with unidirectional wood laminates found in the literature, which is probably linked to the excellent interface observed with SEM.
Effects of Surface Treatments and Cement Type on Shear Bond Strength between Titanium Alloy and All-Ceramic Materials
Authors: Tuncer Berkcan , Aktas Guliz , Baris Guncu Mustafa , Deniz Diler , Muhtarogullari Mehmet , Al-Haj Husain Nadin , Özcan Mutlu
Published: September 2023

This study aimed to evaluate the effects of surface treatments and resin cement on the adhesion of ceramic and ceramic-like materials to titanium. A total of 40 specimens (5 mm diameter) of each material (lithium disilicate glass ceramic (LDGC—IPS e.maxCAD), lithium silicate glass ceramic (LSGC—VITA Suprinity) and a polymer-infiltrated ceramic network (PICN—Vita Enamic)) were fabricated using CAD/CAM technologies. In total, 120 titanium (Ti) specimens were divided into 12 groups, and half of the titanium specimens were tribochemically coated using CoJet. The titanium and all-ceramic specimens were cemented using either Self-curing adhesive cement (SCAC—Panavia 21) or a Self-curing luting composite (SCLC—Multilink Hybrid Abutment). After 5000 cycles of thermal aging, the shear bond strength (SBS) test was conducted using a universal testing machine. The failure modes of the specimens were analyzed using stereomicroscopy, and additionally, the representative specimens were observed using Scanning Electron Microscopy. ANOVA was used for the statistical analysis (p < 0.05). The post-hoc Duncan test was used to determine significant differences between the groups. The mean SBS values (mean ± STD) ranged from 15 ± 2 MPa to 29 ± 6 MPa. Significantly higher SBS values were acquired when the titanium surface was tribochemically coated (p < 0.05). The SCLC showed higher SBS values compared to the SCAC. While the LDGC showed the highest SBS values, the PICN presented the lowest. The tribochemical coating on the cementation surfaces of the titanium increased the SBS values. The specimens cemented with the SCLC showed higher SBS values than those with the SCAC. Additionally, the SCLC cement revealed a more significant increase in SBS values when used with the LDGC. The material used for restoration has a high impact on SBS than those of the cement and surface conditioning.
Investigation of the Fabrication of Diamond/SiC Composites Using α-Si3N4/Si Infiltration
Authors: Xing Bo , Zhang Yingfan , Zhao Jinzhui , Wang Jianyu , Huang Guoqin
Published: September 2023

Diamond/SiC (Dia/SiC) composites possess excellent properties, such as high thermal conductivity and low thermal expansion coefficient. In addition, they are suitable as electronic packaging materials. This study mainly optimized the diamond particle size packing and liquid-phase silicon infiltration processes and investigated a method to prevent the adhesion of the product to molten silicon. Based on the Dinger–Funk particle stacking theory, a multiscale diamond ratio optimization model was established, and the volume ratio of diamond particles with sizes of D20, D50, and D90 was optimized as 1:3:6. The method of pressureless silicon infiltration and the formulas of the composites were investigated. The influences of bedding powder on phase composition and microstructure were studied using X-ray diffraction and scanning electron microscopy, and the optimal parameters were obtained. The porosity of the preform was controlled by regulating the feeding amount through constant volume molding. Dia/SiC-8 exhibited the highest density of 2.73 g/cm3 and the lowest porosity of 0.6%. To avoid adhesion between the sample and buried powder with the bedding silicon powder, a mixed powder of α-Si3N4 and silicon was used as the buried powder and the related mechanisms of action were discussed.
Filament-Reinforced 3D Printing of Clay
Authors: Jauk Julian , Gosch Lukas , Vašatko Hana , Königsberger Markus , Schlusche Johannes , Stavric Milena
Published: September 2023

This research resulted in the development of a method that can be used for filament-reinforced 3D printing of clay. Currently, clay-based elements are mixed with randomly dispersed fibrous materials in order to increase their tensile strength. The advantages of taking this new approach to create filament-reinforced prints are the increased bridging ability while printing, the increased tensile strength of the dried elements, and the achievement of non-catastrophic failure behavior. The research methodology used involves the following steps: (1) evaluating properties of various filament materials with respect to multiple criteria, (2) designing a filament guiding nozzle for co-extrusion, and (3) conducting a comprehensive testing phase for the composite material. This phase involves comparisons of bridging ability, tensile strength evaluations for un-reinforced clay prints and filament-reinforced prints, as well as the successful production of an architectural brick prototype. (4) Finally, the gathered results are subjected to thorough analysis. Compared to conventional 3D printing of clay, the developed method enables a substantial increase in bridging distance during printing by a factor of 460%. This capability facilitates the design of objects characterized by reduced solidity and the attainment of a more open, lightweight, and net-like structure. Further, results show that the average tensile strength of the reinforced sample in a dry state exhibited an enhancement of approximately 15%. The combination of clay’s ability to resist compression and the filament’s capacity to withstand tension has led to the development of a structural concept in this composite material akin to that of reinforced concrete. This suggests its potential application within the construction industry. Producing the prototype presented in this research would not have been possible with existing 3D printing methods of clay.
Characterizing the Effect of Freeze–Thaw Cycling on Pore Structure of Asphalt Concrete Mixtures Using X-ray CT Scanning
Authors: Alawneh Mai , Soliman Haithem , Anthony Ania
Published: September 2023

Freeze–thaw (F–T) cycling presents a challenge when building durable pavement structures in cold regions. Understanding the changes within the microstructure of asphalt concrete (AC) due to F–T conditions is crucial for developing a resilient pavement design. This study investigates the impact of F–T cycles on five AC mixtures using X-ray computed tomography (CT) scanning. Image analysis was completed to evaluate the changes in the microstructure of the AC samples before and after exposure to 30, 60, and 90 F–T cycles. The changes/degradation in the microstructure were evaluated based on analyzing the distribution and properties of air voids within the AC samples. The results showed that an X-ray CT scan can successfully capture the impact of F–T cycles on the structure of air voids in different AC mixtures. The findings of this research provide guidelines for understanding the mechanism of F–T damage within AC, which can assist in optimizing the performance of AC in cold regions.
Repair Strategy for Epoxy Anticorrosive Coatings on Steel Structures
Authors: Tu Kun , Wu Jin , Zhao Xing , Zhang Lifang , Zhang Zehui
Published: September 2023

This paper presents the results of a test of epoxy anticorrosion coating repair. Two strategies of coating repair were studied, respectively: partial repair and integral repair. The gloss loss rate, color difference and rust area rate of the repair coating were measured. The anticorrosion performance of repair coatings under different repair methods was compared. Based on the results of the coating repair test, the repair criteria for coatings were defined, and the repair strategy for epoxy anticorrosive coatings on steel structure was proposed. The results show that Marathon 500 super abrasion resistant epoxy paint (M500) and Jotamastic 90 GF low surface treatment epoxy abrasion resistant glass flake paint (J90GF) are suitable for partial repair of epoxy anticorrosive coatings on steel structures, and that Jotamastic 90 low surface treatment epoxy abrasion resistant coating (J90) and Marathon 500 super abrasion resistant epoxy paint (M500) are suitable for integral repair of epoxy anticorrosive coatings on steel structures.
Research on the Development of a Way to Modify Asphalt Mixtures with PET Recyclates
Authors: Majka Tomasz M. , Ostrowski Krzysztof Adam , Piechaczek Marcin
Published: September 2023

Due to the growing need to recycle plastics, new possibilities for their reuse are intensively sought. In the Asian market, waste polymers are increasingly used to modify road bitumen. This solution is beneficial in many aspects, especially in economic and ecological terms. In this work, recycled poly(ethylene terephthalate) (RPET), obtained from storage points located in Lesser Poland, was subjected to material recycling, and its properties were examined using three analyses: differential scanning calorimetry (DSC), thermogravimetric analysis (TG), and Fourier transform infrared spectroscopy (FTIR). The most important point of this research was the selection of conditions for obtaining modified asphalt mixtures through the addition of RPET. Subsequently, the effect of the polymer on the properties of road bitumens was assessed on the basis of penetration tests, softening point, elastic recovery, and structure. In the last stage of our research work, asphalt mixtures with the addition of modified waste PET (PMA) containing mineral filler in the form of basalt dust were obtained. The properties of the obtained mineral–polymer–asphalt mixtures were compared in terms of frost resistance, structure, and abrasion resistance with the properties of mineral–asphalt mixtures that were taken from damaged road surfaces in four points in the city of Tarnów (Lesser Poland) in the winter of 2022. It has been shown that the modification of road bitumen with the use of recyclate and mineral filler has a significant impact on its performance properties.
Study on Rolling Defects of Al-Mg Alloys with High Mg Content in Normal Rolling and Cross-Rolling Processes
Authors: Lim Seong-Sik , Hong Je-Pyo , Kim Minki , Park Young-Chul , Lee Sang-Mock , Cho Dae-Yeon , Cho Chang-Hee
Published: September 2023

This study investigated defect formation and strain distribution in high-Mg-content Al-Mg alloys during normal rolling and cross-rolling processes. The finite element analysis (FEA) revealed the presence of wave defects and strain localization-induced zipper cracks in normal cold rolling, which were confirmed by the experimental results. The concentration of shear strain played a significant role in crack formation and propagation. However, the influence of wave defects was minimal in the cross-rolling process, which exhibited a relatively uniform strain distribution. Nonetheless, strain concentration at the edge and center regions led to the formation of zipper cracks and edge cracks, with more pronounced propagation observed in the experiments compared to FEA predictions. Furthermore, texture evolution was found to be a crucial factor affecting crack propagation, particularly with the development of the Goss texture component, which was observed via electron backscattered diffraction analysis at bending points. The Goss texture hindered crack propagation, while the Brass texture allowed cracks to pass through. This phenomenon was consistent with both FEA and experimental observations. To mitigate edge crack formation and propagation, potential strategies involve promoting the formation of the Goss texture at the edge through alloy and process conditions, as well as implementing intermediate annealing to alleviate stress accumulation. These measures can enhance the overall quality and reliability of Al-Mg alloys during cross-rolling processes. In summary, understanding the mechanisms of defect formation and strain distribution in Al-Mg alloys during rolling processes is crucial for optimizing their mechanical properties. The findings of this study provide insights into the challenges associated with wave defects, strain localization, and crack propagation. Future research and optimization efforts should focus on implementing strategies to minimize defects and improve the overall quality of Al-Mg alloys in industrial applications.
TiO2 Nanotubes Decorated with Mo2C for Enhanced Photoelectrochemical Water-Splitting Properties
Authors: Moridon Siti Nurul Falaein , Arifin Khuzaimah , Mohamed Mohamad Azuwa , Minggu Lorna Jeffery , Mohamad Yunus Rozan , Kassim Mohammad B.
Published: September 2023

The presence of Ti3+ in the structure of TiO2 nanotube arrays (NTs) has been shown to enhance the photoelectrochemical (PEC) water-splitting performance of these NTs, leading to improved results compared to pristine anatase TiO2 NTs. To further improve the properties related to PEC performance, we successfully produced TiO2 NTs using a two-step electrochemical anodization technique, followed by annealing at a temperature of 450 °C. Subsequently, Mo2C was decorated onto the NTs by dip coating them with precursors at varying concentrations and times. The presence of anatase TiO2 and Ti3O5 phases within the TiO2 NTs was confirmed through X-ray diffraction (XRD) analysis. The TiO2 NTs that were decorated with Mo2C demonstrated a photocurrent density of approximately 1.4 mA cm−2, a value that is approximately five times greater than the photocurrent density exhibited by the bare TiO2 NTs, which was approximately 0.21 mA cm−2. The observed increase in photocurrent density can be ascribed to the incorporation of Mo2C as a cocatalyst, which significantly enhances the photocatalytic characteristics of the TiO2 NTs. The successful deposition of Mo2C onto the TiO2 NTs was further corroborated by the characterization techniques utilized. The utilization of field emission scanning electron microscopy (FESEM) allowed for the observation of Mo2C particles on the surface of TiO2 NTs. To validate the composition and optical characteristics of the decorated NTs, X-ray photoelectron spectroscopy (XPS) and UV absorbance analysis were performed. This study introduces a potentially effective method for developing efficient photoelectrodes based on TiO2 for environmentally sustainable hydrogen production through the use of photoelectrochemical water-splitting devices. The utilization of Mo2C as a cocatalyst on TiO2 NTs presents opportunities for the advancement of effective and environmentally friendly photoelectrochemical (PEC) systems.
Synthesis and Evaluation of Properties of an Additive Based on Bismuth Titanates for Cement Systems
Authors: Samchenko Svetlana V. , Kozlova Irina V. , Korshunov Andrey V. , Zemskova Olga V. , Dudareva Marina O.
Published: September 2023

The development of modern building materials science involves the process of designing innovative materials that exhibit unique characteristics, such as energy efficiency, environmental friendliness, self-healing ability, and photocatalytic properties. This can be achieved by modifying cement with nano- and fine-dispersed additives that can give the material new properties. Such additives include a number of compounds based on the TiO2-Bi2O3 system. These compounds have photocatalytic activity in the near-UV and visible range of the spectrum, which can serve to create photocatalytic concretes. Here, the purpose of this scientific study was to synthesize compounds based on the TiO2-Bi2O3 system using two methods in order to identify the most optimal variant for creating a composite material and determine its properties. Within the framework of this article, two methods of obtaining a photocatalytically active additive based on the TiO2-Bi2O3 system are considered: the solid-state and citrate-based methods. The photocatalytic, mechanical and structural properties of composites containing the synthesized additive are investigated. In this study, it was found that for the creation of photocatalytic concretes, it is advisable to use cement compositions with a bismuth titanate content of 3–10 wt.%. of the cement content, regardless of the method of obtaining the additive. However, the most optimal composition is one containing 5 wt.% of the synthesized additive. It is noted that compositions containing 5% by weight of bismuth titanate demonstrate photocatalytic activity and also show an increase in strength on the first day of hardening by 10% for the solid-state method and 16% for the citrate method.
Generalized Pandemic Model with COVID-19 for Early-Stage Infection Forecasting
Authors: Ponce-Flores Mirna Patricia , Terán-Villanueva Jesús David , Ibarra-Martínez Salvador , Castán-Rocha José Antonio
Published: September 2023

In this paper, we tackle the problem of forecasting future pandemics by training models with a COVID-19 time series. We tested this approach by producing one model and using it to forecast a non-trained time series; however, we limited this paper to the eight states with the highest population density in Mexico. We propose a generalized pandemic forecasting framework that transforms the time series into a dataset via three different transformations using random forest and backward transformations. Additionally, we tested the impact of the horizon and dataset window sizes for the training phase. A Wilcoxon test showed that the best transformation technique statistically outperformed the other two transformations with 100% certainty. The best transformation included the accumulated efforts of the other two plus a normalization that helped rescale the non-trained time series, improving the sMAPE from the value of 25.48 attained for the second-best transformation to 13.53. The figures in the experimentation section show promising results regarding the possibility of forecasting the early stages of future pandemics with trained data from the COVID-19 time series.
Retrial Queueing System for Analyzing Impact of Priority Ultra-Reliable Low-Latency Communication Transmission on Enhanced Mobile Broadband Quality of Service Degradation in 5G Networks
Authors: Makeeva Elena , Kochetkova Irina , Alkanhel Reem
Published: September 2023

Fifth generation (5G) networks support ultra-reliable low-latency communications (URLLC) and enhanced mobile broadband (eMBB). The coexistence of URLLC and eMBB is often organized by non-orthogonal multiple access (NOMA), giving priority to URLLC and resulting in eMBB quality of service (QoS) degradation. In this paper, we address the issue of joint URLLC and eMBB transmission, focusing on the problem from the perspective of delay-tolerant eMBB. Due to the priority given to URLLC, we assume that an eMBB session may be interrupted if there are no free resources available for URLLC or delayed when a new eMBB session arrives. To make the scheme more flexible, we propose that interrupted and delayed eMBB sessions periodically check for free resources, rather than continuously. To analyze this scenario, we propose a retrial queuing system with two retrial buffers (orbits) for interrupted and delayed eMBB sessions. The stationary probability distribution, provided in matrix form by recursive formulas, is presented. The paper concludes with a numerical example showing that the scheme with two buffers, compared to one buffer, practically doubles the average number of active eMBB sessions while keeping the interruption probability below 0.001. We provide an illustration of the configuration of eMBB retrial rates to meet its QoS requirements.
Variational Bayesian Inference for Quantile Regression Models with Nonignorable Missing Data
Authors: Li Xiaoning , Tuerde Mulati , Hu Xijian
Published: September 2023

Quantile regression models are remarkable structures for conducting regression analyses when the data are subject to missingness. Missing values occur because of various factors like missing completely at random, missing at random, or missing not at random. All these may result from system malfunction during data collection or human error during data preprocessing. Nevertheless, it is important to deal with missing values before analyzing data since ignoring or omitting missing values may result in biased or misinformed analysis. This paper studies quantile regressions from a Bayesian perspective. By proposing a hierarchical model framework, we develop an alternative approach based on deterministic variational Bayes approximations. Logistic and probit models are adopted to specify propensity scores for missing manifests and covariates, respectively. Bayesian variable selection method is proposed to recognize significant covariates. Several simulation studies and real examples illustrate the advantages of the proposed methodology and offer some possible future research directions.
LB-GLAT: Long-Term Bi-Graph Layer Attention Convolutional Network for Anti-Money Laundering in Transactional Blockchain
Authors: Guo Chaopeng , Zhang Sijia , Zhang Pengyi , Alkubati Mohammed , Song Jie
Published: September 2023

The decentralization and anonymity of blockchain have attracted significant attention. However, in recent years, there has been a rise in blockchain money laundering incidents, and anti-money laundering efforts have become crucial within the blockchain space. Blockchain money laundering differs from traditional financial money laundering as it does not provide account information, particularly in the case of Bitcoin. This absence of information makes it challenging for researchers to detect money laundering activities based on transaction data. We propose LB-GLAT, a novel Long-Term Bi-Graph Layer Attention Convolutional Network, to effectively capture the topological structure and attribute characteristics of money laundering on the blockchain transaction graph. LB-GLAT utilizes the transaction graph and the reverse transaction graph to solve the no-loop problem that results in the inability to capture the destination of blockchain transactions and designs a long-term layer attention mechanism to alleviate the over-smoothing problem. We implemented a series of experiments to evaluate LB-GLAT, which achieved state-of-art performance compared with other methods, presenting an accuracy of 0.9776, a precision of 0.9317, a recall of 0.8494, an F1−score of 0.8887, and an AUC of 0.9806.
A Mathematical Model for Customer Segmentation Leveraging Deep Learning, Explainable AI, and RFM Analysis in Targeted Marketing
Authors: Talaat Fatma M. , Aljadani Abdussalam , Alharthi Bshair , Farsi Mohammed A. , Badawy Mahmoud , Elhosseini Mostafa
Published: September 2023

In the evolving landscape of targeted marketing, integrating deep learning (DL) and explainable AI (XAI) offers a promising avenue for enhanced customer segmentation. This paper introduces a groundbreaking approach, DeepLimeSeg, which synergizes DL methodologies with Lime-based Explainability to segment customers effectively. The approach employs a comprehensive mathematical model to harness demographic data, behavioral patterns, and purchase histories, categorizing customers into distinct clusters aligned with their preferences and needs. A pivotal component of this research is the mathematical underpinning of the DeepLimeSeg approach. The Lime-based Explainability module ensures that the segmentation results are accurate and interpretable. The mathematical rigor facilitates businesses tailoring their marketing strategies with precision, optimizing sales outcomes. To validate the efficacy of DeepLimeSeg, we employed two real-world datasets: Mall-Customer Segmentation Data and an E-Commerce dataset. A comparative analysis between DeepLimeSeg and the traditional Recency, Frequency, and Monetary (RFM) analysis is presented. The RFM analysis, grounded in its mathematical modeling, segments customers based on purchase recency, frequency, and monetary value. Our preprocessing involved computing RFM scores for each customer, followed by K-means clustering to delineate customer segments. Empirical results underscored the superiority of DeepLimeSeg over other models in terms of MSE, MAE, and R2 metrics. Specifically, the model registered an MSE of 0.9412, indicative of its robust predictive accuracy concerning the spending score. The MAE value stood at 0.9874, signifying minimal deviation from actual values. This paper accentuates the importance of mathematical modeling in enhancing customer segmentation. The DeepLimeSeg approach, with its mathematical foundation and explainable AI integration, paves the way for businesses to make informed, data-driven marketing decisions.
Six-Segment Strategy for Prosumers’ Financial Benefit Maximization in Local Peer-to-Peer Energy Trading
Authors: Mochi Pratik , Pandya Kartik , Faia Ricardo , Soares Joao
Published: September 2023

The notion of prosumers, people who create and consume energy, has emerged in the energy sector as a result of the fast integration of renewable energy sources and advances in digital technology. Platforms for peer-to-peer (P2P) energy trading have come to light as viable ways to allow prosumers to conduct direct energy transactions within small groups. Existing P2P trading models, however, frequently lack an optimized approach to maximize the advantages for prosumers. In this article, we provide a novel six-segment strategy (SSS) that is intended to increase prosumers′ ability to maximize their benefits in P2P energy trading systems. Additionally, the SSS promotes prosumers′ active market engagement by supporting community-driven energy exchanges. Through extensive mathematical modeling, simulations, and case studies, we demonstrate the effectiveness of the six-segment strategy in enhancing the economic benefits of prosumers participating in P2P energy trading. The proposed optimization strategy holds the potential to revolutionize the energy landscape by promoting more sustainable and consumer-centric energy trading. The cost savings of 12.9% are distributed among prosumers by the SSS, which is an improvement compared with previously proposed strategies.
An Adaptive Inertia and Damping Control Strategy Based on Enhanced Virtual Synchronous Generator Model
Authors: Suvorov Aleksey , Askarov Alisher , Ruban Nikolay , Rudnik Vladimir , Radko Pavel , Achitaev Andrey , Suslov Konstantin
Published: September 2023

In modern converter-dominated power systems, total inertia is very variable and depends on the share of power generated by renewable-based converter-interfaced generation (CIG) at each specific moment. As a result, the limits required by the grid codes on the rate of change of frequency and its nadir or zenith during disturbances become challenging to achieve with conventional control approaches. Therefore, the transition to a novel control strategy of CIG with a grid-forming power converter is relevant. For this purpose, a control algorithm based on a virtual synchronous generator (VSG) is used, which simulates the properties and capabilities of a conventional synchronous generation. However, due to continuously changing operating conditions in converter-dominated power systems, the virtual inertia formed by VSG must be adaptive. At the same time, the efficiency of adaptive algorithms strongly depends on the used VSG structure. In this connection, this paper proposes an enhanced VSG structure for which the transfer function of the active power control loop was formed. With the help of it, the advantages over the conventional VSG structure were proven, which are necessary for the effective adaptive control of the VSG parameters. Then, the analysis of the impact of the VSG parameters on the dynamic response using the transient characteristics in the time domain was performed. Based on the results obtained, adaptive algorithms for independent control of the virtual inertia and the parameters of the VSG damper winding were developed. The performed mathematical modeling confirmed the reliable and effective operation of the developed adaptive control algorithms and the enhanced VSG structure. The theoretical and experimental results obtained in this paper indicate the need for simultaneous development and improvement of both adaptive control algorithms and VSG structures used for this purpose.
Numerical Method for Solving the Nonlinear Superdiffusion Equation with Functional Delay
Authors: Pimenov Vladimir , Lekomtsev Andrei
Published: September 2023

For a space-fractional diffusion equation with a nonlinear superdiffusion coefficient and with the presence of a delay effect, the grid numerical method is constructed. Interpolation and extrapolation procedures are used to account for the functional delay. At each time step, the algorithm reduces to solving a linear system with a main matrix that has diagonal dominance. The convergence of the method in the maximum norm is proved. The results of numerical experiments with constant and variable delays are presented.
On the Cauchy Problem for Pseudohyperbolic Equations with Lower Order Terms
Authors: Bondar Lina N. , Demidenko Gennadii V.
Published: September 2023

We consider a class of strictly pseudohyperbolic equations with lower order terms. The solvability of the Cauchy problem in Sobolev spaces with special weights is established. The uniqueness of the solution is proven and estimates are obtained.
A Quantum-Resistant Blockchain System: A Comparative Analysis
Authors: Thanalakshmi P. , Rishikhesh A. , Marion Marceline Joel , Joshi Gyanendra Prasad , Cho Woong
Published: September 2023

Blockchain transactions are decentralized, secure, and transparent, and they have altered industries. However, the emergence of quantum computing presents a severe security risk to the traditional encryption algorithms used in blockchain. Post-quantum signatures are required to preserve integrity and reliability. Furthermore, combining the InterPlanetary File System (IPFS) with blockchain provides a long-term strategy for data storage and sharing. This study investigates the integration of post-quantum signatures with the IPFS in a blockchain system, which can considerably enhance blockchain system efficiency. We increase security and efficiency by recording hash values of signatures and public keys within the blockchain and storing their actual content using the IPFS. The study compares NIST-recommended post-quantum signatures with the ECDSA in a Bitcoin exchange scheme to show how effective the system is in countering quantum threats while maintaining optimal performance. This research makes an important addition to the long-term viability and dependability of blockchain technology in the face of the growing landscape of quantum computing breakthroughs.
Algebraic Solution of Tropical Best Approximation Problems
Authors: Krivulin Nikolai
Published: September 2023

We introduce new discrete best approximation problems, formulated and solved in the framework of tropical algebra, which deals with semirings and semifields with idempotent addition. Given a set of samples, each consisting of the input and output of an unknown function defined on an idempotent semifield, the problem is to find a best approximation of the function, by tropical Puiseux polynomial and rational functions. A new solution approach is proposed, which involves the reduction of the problem of polynomial approximation to the best approximate solution of a tropical linear vector equation with an unknown vector on one side (a one-sided equation). We derive a best approximate solution to the one-sided equation, and we evaluate the inherent approximation error in a direct analytical form. Furthermore, we reduce the rational approximation problem to the best approximate solution of an equation with unknown vectors on both sides (a two-sided equation). A best approximate solution to the two-sided equation is obtained in numerical form, by using an iterative alternating algorithm. To illustrate the new technique developed, we solve example approximation problems in terms of a real semifield, where addition is defined as maximum and multiplication as arithmetic addition (max-plus algebra), which corresponds to the best Chebyshev approximation by piecewise linear functions.
One-Step Clustering with Adaptively Local Kernels and a Neighborhood Kernel
Authors: Chen Cuiling , Hu Zhijun , Xiao Hongbin , Ma Junbo , Li Zhi
Published: September 2023

Among the methods of multiple kernel clustering (MKC), some adopt a neighborhood kernel as the optimal kernel, and some use local base kernels to generate an optimal kernel. However, these two methods are not synthetically combined together to leverage their advantages, which affects the quality of the optimal kernel. Furthermore, most existing MKC methods require a two-step strategy to cluster, i.e., first learn an indicator matrix, then executive clustering. This does not guarantee the optimality of the final results. To overcome the above drawbacks, a one-step clustering with adaptively local kernels and a neighborhood kernel (OSC-ALK-ONK) is proposed in this paper, where the two methods are combined together to produce an optimal kernel. In particular, the neighborhood kernel improves the expression capability of the optimal kernel and enlarges its search range, and local base kernels avoid the redundancy of base kernels and promote their variety. Accordingly, the quality of the optimal kernel is enhanced. Further, a soft block diagonal (BD) regularizer is utilized to encourage the indicator matrix to be BD. It is helpful to obtain explicit clustering results directly and achieve one-step clustering, then overcome the disadvantage of the two-step strategy. In addition, extensive experiments on eight data sets and comparisons with six clustering methods show that OSC-ALK-ONK is effective.
Asymptotic Stability and Dependency of a Class of Hybrid Functional Integral Equations
Authors: El-Sayed Ahmed M. A. , Ba-Ali Malak M. S. , Hamdallah Eman M. A.
Published: September 2023

Here, we discuss the solvability of a class of hybrid functional integral equations by applying Darbo’s fixed point theorem and the technique of the measure of noncompactness (MNC). This study has been located in space BC (R+). Furthermore, we prove the asymptotic stability of the solution of our problem on R+. We introduce the idea of asymptotic dependency of the solutions on some parameters for that class. Moreover, general discussion, examples, and remarks are demonstrated.
Memory-Efficient Discrete Cosine Transform Domain Weight Modulation Transformer for Arbitrary-Scale Super-Resolution
Authors: Kim Min Hyuk , Yoo Seok Bong
Published: September 2023

Recently, several arbitrary-scale models have been proposed for single-image super-resolution. Furthermore, the importance of arbitrary-scale single image super-resolution is emphasized for applications such as satellite image processing, HR display, and video-based surveillance. However, the baseline integer-scale model must be retrained to fit the existing network, and the learning speed is slow. This paper proposes a network to solve these problems, processing super-resolution by restoring the high-frequency information lost in the remaining arbitrary-scale while maintaining the baseline integer scale. The proposed network extends an integer-scaled image to an arbitrary-scale target in the discrete cosine transform spectral domain. We also modulate the high-frequency restoration weights of the depthwise multi-head attention to use memory efficiently. Finally, we demonstrate the performance through experiments with existing state-of-the-art models and their flexibility through integration with existing integer-scale models in terms of peak signal-to-noise ratio (PSNR) and similarity index measure (SSIM) scores. This means that the proposed network restores high-resolution (HR) images appropriately by improving the image sharpness of low-resolution (LR) images.
Equilibrium Analysis for Batch Service Queueing Systems with Strategic Choice of Batch Size
Authors: Nakamura Ayane , Phung-Duc  Tuan
Published: September 2023

Various transportation services exist, such as ride-sharing or shared taxis, in which customers receive services in a batch of flexible sizes and share fees. In this study, we conducted an equilibrium analysis of a variable batch service model in which customers who observe no waiting customers in an incomplete batch can strategically select a batch size to maximize the individual utilities. We formulated this model as a three-dimensional Markov chain and created a book-type transition diagram. To consider the joining/balking dilemma of customers for this model, we proposed an effective algorithm to construct a necessary and sufficient size of state space for the Markov chain provided that all customers adopt the threshold-type equilibrium strategy. Moreover, we proved that the best batch size is a non-decreasing function for i if the reward for the completion of batch service with size l is an increasing function of l assuming that a tagged customer observes i complete batches in the system upon arrival; in other words, the fee decreases as the batch becomes larger. We then derive several performance measures, such as throughput, social welfare, and monopolist’s revenue. Throughout the numerical experiment, a comparison between the present variable batch service model and regular batch service model in which customers were served in a constant batch, was discussed. It was demonstrated that the three performance measures can be optimized simultaneously in the variable batch service model, as long as the fee was set relatively high.
Fitting an Equation to Data Impartially
Authors: Tofallis Chris
Published: September 2023

We consider the problem of fitting a relationship (e.g., a potential scientific law) to data involving multiple variables. Ordinary (least squares) regression is not suitable for this because the estimated relationship will differ according to which variable is chosen as being dependent, and the dependent variable is unrealistically assumed to be the only variable which has any measurement error (noise). We present a very general method for estimating a linear functional relationship between multiple noisy variables, which are treated impartially, i.e., no distinction between dependent and independent variables. The data are not assumed to follow any distribution, but all variables are treated as being equally reliable. Our approach extends the geometric mean functional relationship to multiple dimensions. This is especially useful with variables measured in different units, as it is naturally scale invariant, whereas orthogonal regression is not. This is because our approach is not based on minimizing distances, but on the symmetric concept of correlation. The estimated coefficients are easily obtained from the covariances or correlations, and correspond to geometric means of associated least squares coefficients. The ease of calculation will hopefully allow widespread application of impartial fitting to estimate relationships in a neutral way.
Oscillator with Time-Variable Degree of Nonlinearity: Theory and Application in Aging of Polymer Composite Structure
Authors: Cveticanin L. , Zukovic M.
Published: September 2023

In this paper, a new type of one-degree-of-freedom pure nonlinear oscillator with a time variable degree of nonlinearity is introduced. Namely, the degree of the nonlinearity in the restitution force is not a constant but a ‘slow time’ variable function. The mathematical model is a second-order nonlinear differential equation with time-variable parameters. An approximate solving procedure based on the method of time-variable amplitude, frequency and phase is developed. It is found that the vibration properties depend on initial conditions and the degree of time-variable function. The theoretical results are tested on almost linear, cubic and high-degree nonlinear oscillators. According to theoretical considerations, the process of aging in fiber-reinforced polymer composite structure is investigated. It is found that the amplitude and the frequency of vibration of the reinforced polymer structure decrease over time. The result is in good agreement with already published experimental data. The additional conclusion of the research is that the oscillator model suggested in the paper is suitable for the prediction of mechanic properties of the polymer structure in aging and also in similar destructive processes.
Effects of Temperature, Light and Salt on the Production of Fucoxanthin from Conticribra weissflogii
Authors: Li Feng , Rui Xiangyu , Amenorfenyo David Kwame , Pan Yao , Huang Xianghu , Li Changling
Published: September 2023

Fucoxanthin is a natural active substance derived from diatoms that is beneficial to the growth and immunity of humans and aquatic animals. Temperature, light and salinity are important environmental factors affecting the accumulation of diatom actives; however, their effects on the production of fucoxanthin in C. weissflogii are unclear. In this study, single-factor experiments are designed and followed by an orthogonal experiment to determine the optimal combination of fucoxanthin production conditions in C. weissflogii. The results showed that the optimum conditions for fucoxanthin production were a temperature of 30 °C, a light intensity of 30 umol m−2 s−1 and a salinity of 25. Under these conditions, the cell density, biomass, carotenoid content and fucoxanthin content of C. weissflogii reached 1.97 × 106 cell mL−1, 0.76 g L−1, 2.209 mg L−1 and 1.372 mg g−1, respectively, which were increased to 1.53, 1.71, 2.50 and 1.48 times higher than their initial content. The work sought to give useful information that will lead to an improved understanding of the effective method of cultivation of C. weissflogii for natural fucoxanthin production.