Traditional agricultural irrigation systems waste significant amounts of water and energy due to inefficient scheduling and the absence of real-time monitoring capabilities.This research developed a comprehensive IoT-...Traditional agricultural irrigation systems waste significant amounts of water and energy due to inefficient scheduling and the absence of real-time monitoring capabilities.This research developed a comprehensive IoT-based smart irrigation control systemto optimize water and energy management in agricultural greenhouses while enhancing crop productivity.The system employs a sophisticated four-layer Internet ofThings(IoT)architecture based on an ESP32 microcontroller,integrated with multiple environmental sensors,including soil moisture,temperature,humidity,and light intensity sensors,for comprehensive environmental monitoring.The system utilizes the Message Queuing Telemetry Transport(MQTT)communication protocol for reliable data transmission and incorporates a Random Forest machine learning algorithm for automated irrigation decision-making processes.The Random Forest model achieved exceptional performance with 99.3%overall accuracy,demonstrating high model reliability.Six operational modules were developed and implemented with three distinct control methods:manual operation,condition-based automatic control,and AI-driven intelligent control systems.A comprehensive one-month comparative analysis demonstrated remarkable improvements across multiple performance metrics:a 50%reduction in both water consumption(from 140 to 70 L/day)and energy usage(from 7.00 to 3.50 kWh/day),a substantial 130%increase in water use efficiency,and a significant 50%decrease in CO_(2) emissions.Furthermore,detailed factor importance analysis revealed soil moisture as the primary decision factor(38.6%),followed by temporal factors(20.3%)and light intensity(18.4%).The system demonstrates exceptional potential for annual energy conservation of 1277.5 kWh and CO_(2) emission reduction of 638.75 kg,contributing substantially to sustainable development goals and advancing smart agriculture technologies.展开更多
The metaverse has become a very important phenomenon in society because of the emergence of new technologies. The widespread adoption of the metaverse has generated significant discussions about the challenges and opp...The metaverse has become a very important phenomenon in society because of the emergence of new technologies. The widespread adoption of the metaverse has generated significant discussions about the challenges and opportunities it presents. We invited three panelists to present their personal viewpoints on the metaverse in the 2022 AIS-SIG-ISAP Workshop on Information Systems in Asia-Pacific (ISAP). The discussion indicated that metaverse research is being conducted. Furthermore, it highlighted new research directions and offered research topics related to the advantages or disadvantages of the metaverse. The proposed research topics will offer new insights to academics and practitioners.展开更多
The recent rapid development of China’s foreign trade has led to the significant increase in waterway transportation and automated container ports. Automated terminals can significantly improve the loading and unload...The recent rapid development of China’s foreign trade has led to the significant increase in waterway transportation and automated container ports. Automated terminals can significantly improve the loading and unloading efficiency of container terminals. These terminals can also increase the port’s transportation volume while ensuring the quality of cargo loading and unloading, which has become an inevitable trend in the future development of ports. However, the continuous growth of the port’s transportation volume has increased the horizontal transportation pressure on the automated terminal, and the problems of route conflicts and road locks faced by automated guided vehicles (AGV) have become increasingly prominent. Accordingly, this work takes Xiamen Yuanhai automated container terminal as an example. This work focuses on analyzing the interference problem of path conflict in its horizontal transportation AGV scheduling. Results show that path conflict, the most prominent interference factor, will cause AGV scheduling to be unable to execute the original plan. Consequently, the disruption management was used to establish a disturbance recovery model, and the Dijkstra algorithm for combining with time windows is adopted to plan a conflict-free path. Based on the comparison with the rescheduling method, the research obtains that the deviation of the transportation path and the deviation degree of the transportation path under the disruption management method are much lower than those of the rescheduling method. The transportation path deviation degree of the disruption management method is only 5.56%. Meanwhile, the deviation degree of the transportation path under the rescheduling method is 44.44%.展开更多
Aiming at the problem that existing models in aspect-level sentiment analysis cannot fully and effectively utilize sentence semantic and syntactic structure information, this paper proposes a graph neural network-base...Aiming at the problem that existing models in aspect-level sentiment analysis cannot fully and effectively utilize sentence semantic and syntactic structure information, this paper proposes a graph neural network-based aspect-level sentiment classification model. Self-attention, aspectual word multi-head attention and dependent syntactic relations are fused and the node representations are enhanced with graph convolutional networks to enable the model to fully learn the global semantic and syntactic structural information of sentences. Experimental results show that the model performs well on three public benchmark datasets Rest14, Lap14, and Twitter, improving the accuracy of sentiment classification.展开更多
Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoti...Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoting high-quality development of new energy in China.This paper constructs an evaluation index system for the development of NEVs and the ecological environment.It uses game theory combining weighting model,particle swarm optimized projection tracking evaluation model,coupling coordination degree model,and machine learning algorithms to calculate and analyze the level of coupling coordination development of NEVs and the ecological environment in China from 2010 to 2021,and identifies the driving factors.The research results show that:(i)From 2010 to 2021,the development index of NEVs in China has steadily increased from 0.085 to 0.634,while the ecological environment level index significantly rose from 0.170 to 0.884,reflecting the continuous development of China in both NEVs and the ecological environment.(ii)From 2010 to 2012,the two systems—new energy vehicle(NEV)development and the ecological environment—were in a period of imbalance and decline.From 2013 to 2016,they underwent a transition period,and from 2017 to 2021,they entered a period of coordinated development showing a trend of benign and continuous improvement.By 2021,they reached a good level of coordination.(iii)Indicators such as the number of patents granted for NEVs,water consumption per unit of GDP,and energy consumption per unit of GDP are the main driving factors affecting the coupling coordination development of NEVs and the ecological environment in China.展开更多
The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method f...The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.展开更多
Objective To investigate whether 2,3,5,4'-tetrahydroxystilbene-2-O-β-glucoside(TSG)ameliorated polycystic ovary syndrome(PCOS)-like characteristics by inhibiting inflammation.Methods PCOS models were established ...Objective To investigate whether 2,3,5,4'-tetrahydroxystilbene-2-O-β-glucoside(TSG)ameliorated polycystic ovary syndrome(PCOS)-like characteristics by inhibiting inflammation.Methods PCOS models were established by injecting subcutaneously with dehydroepiandrosterone into female Sprague-Dawley rats,followed by receiving intraperitoneal injection of TSG.The granular cells(GCs)KGN were transfected with small interfering RNAs(si-NC and si-CYP19A1).The cells were preincubated with lipopolysaccharide(LPS)and then treated with or without TSG.The estrous cycle was monitored using vaginal exfoliated cells.The morphology of ovarian follicles was analyzed by H&E staining.ELISA was used to analyze estradiol(E2),testosterone(T),follicle stimulating hormone(FSH),luteinizing hormone(LH),IL-6,TNF-α,AGEs,CRP and Omentin-1 levels in serum.Immunohistochemistry was performed to analyze PCNA and CYP19A1 expressions in the GCs of ovaries.Tunel staining was executed to detect the apoptosis of GCs.Quantitative polymerase chain reaction(qPCR)and Western blot were implemented to measure the expression of CYP19A1 in the ovaries and transfected cells.qPCR was used to analyze the expression of IL-6 and TNF-αin the transfected cells treated with LPS and TSG.Results The estrous cycles were restored in TSG group.Compared with model group,the sinus follicles were reduced and corpus luteums were increased in TSG group.TSG group showed increased E2,and decreased T and LH,compared with model group.Pro-inflammatory factors(IL-6,TNF-α,CRP and AGEs)were decreased,and anti-inflammatory factor(Omentin-1)was increased in TSG group compared with those in model group.TSG could partially inhibit decrease of PNCA-positive GCs and increase of Tunel-positive GCs caused by PCOS.The CYP19A1 expression of GCs in TSG group was upregulated compared with model group.The expressions of IL-6 and TNFαin si-CYP19A1 cells were increased compared with si-NC cells.Compared with cells(si-NC and si-CYP19A1)treated without LPS,the expressions of IL-6 and TNF-αcells were increased,and the expression of CYP19A1 was downregulated in LPS-preincubated cells.Compared with cells treated with LPS,the expression of IL-6 and TNF-αwere decreased,and the expression of CYP19A1 was increased in cells treated with LPS and TSG.Compared with si-NC cells treated with LPS and TSG,the expressions of IL-6 and TNF-αcells were increased in the si-CYP19A1 cells treated with LPS and TSG.Conclusion TSG could alleviate PCOS-like characteristics by increasing the expression of CYP19A1 in GCs to inhibit inflammatory response.展开更多
Purpose:This study examines why papers with high CD indices(measuring research disruptiveness)increasingly show reduced citation impact and investigates whether this represents genuine impact reduction or methodologic...Purpose:This study examines why papers with high CD indices(measuring research disruptiveness)increasingly show reduced citation impact and investigates whether this represents genuine impact reduction or methodological artifacts.Design/methodology/approach:We analyzed 29 million papers(1950-2016)using Poisson regression to examine relationships between the CD index and citation count,with controls for fields,team size,and reference count.Findings:Papers with high CD indices showed reduced citation impact over time.However,when controlling for increasing reference counts in papers,this relationship reversed,revealing a positive association.Papers with more references exhibit lower CD indices owing to the index’s sensitivity to the reference count,while achieving higher citation counts.Alternative innovation metrics consistently show positive correlations with citation impact.Research limitations:The approach may not adequately capture the reduced citation impact of highly disruptive papers with fewer references.The analysis is limited to journal articles and shows correlation rather than causality.Practical implications:The apparent undervaluation of disruptive research stems from methodological artifacts in the CD index calculation driven by evolving reference patterns.Researchers should control for the reference count when using this metric.Originality/value:This study reveals that bias against disruptive research is specific to the CD index’s calculation methodology,identifying reference behavior as the key factor affecting the relationship between disruption metrics and citation impact.展开更多
Hybrid renewable energy systems(HRES)offer cost-effectiveness,low-emission power solutions,and reduced dependence on fossil fuels.However,the renewable energy allocation problem remains challenging due to complex syst...Hybrid renewable energy systems(HRES)offer cost-effectiveness,low-emission power solutions,and reduced dependence on fossil fuels.However,the renewable energy allocation problem remains challenging due to complex system interactions and multiple operational constraints.This study develops a novel Multi-Neighborhood Enhanced Harris Hawks Optimization(MNEHHO)algorithm to address the allocation of HRES components.The proposed approach integrates key technical parameters,including charge-discharge efficiency,storage device configurations,and renewable energy fraction.We formulate a comprehensive mathematical model that simultaneously minimizes levelized energy costs and pollutant emissions while maintaining system reliability.The MNEHHO algorithm employs multiple neighborhood structures to enhance solution diversity and exploration capabilities.The model’s effectiveness is validated through case studies across four distinct institutional energy demand profiles.Results demonstrate that our approach successfully generates practically feasible HRES configurations while achieving significant reductions in costs and emissions compared to conventional methods.The enhanced search mechanisms of MNEHHO show superior performance in avoiding local optima and achieving consistent solutions.Experimental results demonstrate concrete improvements in solution quality(up to 46% improvement in objective value)and computational efficiency(average coefficient of variance of 24%-27%)across diverse institutional settings.This confirms the robustness and scalability of our method under various operational scenarios,providing a reliable framework for solving renewable energy allocation problems.展开更多
This study presents a new approach that advances the algorithm of similarity measures between generalized fuzzy numbers. Following a brief introduction to some properties of the proposed method, a comparative analysis...This study presents a new approach that advances the algorithm of similarity measures between generalized fuzzy numbers. Following a brief introduction to some properties of the proposed method, a comparative analysis based on 36 sets of generalized fuzzy numbers was performed, in which the degree of similarity of the fuzzy numbers was calculated with the proposed method and seven methods established by previous studies in the literature. The results of the analytical comparison show that the proposed similarity outperforms the existing methods by overcoming their drawbacks and yielding accurate outcomes in all calculations of similarity measures under consideration. Finally, in a numerical example that involves recommending cars to customers based on a nine-member linguistic term set, the proposed similarity measure proves to be competent in addressing fuzzy number recommendation problems.展开更多
The paper considers the poor state of the construction industry in UK and ways in which it might improve for all stakeholders.The transition from present state to a desirable future is mapped using the“three horizons...The paper considers the poor state of the construction industry in UK and ways in which it might improve for all stakeholders.The transition from present state to a desirable future is mapped using the“three horizons”and“four capitals”concepts.Servitisation is suggested as a key innovation for engineering systems in buildings,the dominant lifecycle cost area.Digital twinning facilitates this method of provision and blockchain technology can support its commercialisation,enabling payments for service delivered and keeping safe records.展开更多
With the rapid expansion of multimedia data,protecting digital information has become increasingly critical.Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multi...With the rapid expansion of multimedia data,protecting digital information has become increasingly critical.Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multimedia files while enabling full recovery of the original data after extraction.Audio,as a vital medium in communication,entertainment,and information sharing,demands the same level of security as images.However,embedding data in encrypted audio poses unique challenges due to the trade-offs between security,data integrity,and embedding capacity.This paper presents a novel interpolation-based reversible data hiding algorithm for encrypted audio that achieves scalable embedding capacity.By increasing sample density through interpolation,embedding opportunities are significantly enhanced while maintaining encryption throughout the process.The method further integrates multiple most significant bit(multi-MSB)prediction and Huffman coding to optimize compression and embedding efficiency.Experimental results on standard audio datasets demonstrate the proposed algorithm’s ability to embed up to 12.47 bits per sample with over 9.26 bits per sample available for pure embedding capacity,while preserving full reversibility.These results confirm the method’s suitability for secure applications that demand high embedding capacity and perfect reconstruction of original audio.This work advances reversible data hiding in encrypted audio by offering a secure,efficient,and fully reversible data hiding framework.展开更多
The primary motivation for this study is the recent growth and increased interest in artificial intelligence(AI).Despite the widespread recognition of its critical importance,a discernible scientific gap persists with...The primary motivation for this study is the recent growth and increased interest in artificial intelligence(AI).Despite the widespread recognition of its critical importance,a discernible scientific gap persists within the extant scholarly discourse,particularly concerning exhaustive systematic reviews of AI in the aviation industry.This gap spurred a meticulous analysis of 1,213 articles from the Web of Science(WoS)core database for bibliometric knowledge mapping.This analysis highlights China as the primary contributor to publications,with the Nanjing University of Finance and Economics as the leading institution in paper contributions.Lecture Notes in Artificial Intelligence and the IEEE AIAA Digital Avionics System Conference are the leading journals within this domain.This bibliometric research underscores the key focus on air traffic management,human factors,environmental ini-tiatives,training,logistics,flight operations,and safety through co-occurrence and co-citation analyses.A chro-nological examination of keywords reveals a central research trajectory centered on machine learning,models,deep learning,and the impact of automation on human performance in aviation.Burst keyword analysis identifies the leading-edge research on AI within predictive models,unmanned aerial vehicles,object detection,and con-volutional neural networks.The primary objective is to bridge this knowledge gap and gain comprehensive in-sights into AI in the aviation sector.This study delineates the scholarly terrain of AI in aviation using a bibliometric methodology to facilitate this exploration.The results illuminate the current state of research,thereby enhancing academic understanding of developments within this critical domain.Finally,a new con-ceptual framework was constructed based on the primary elements identified in the literature.This framework can assist emerging researchers in identifying the fundamental dimensions of AI in the aviation industry.展开更多
We discuss the findings of Wu et al on the utility of neutrophil-to-lymphocyte ratio,platelet-to-lymphocyte ratio,and systemic immune-inflammatory index as diagnostic markers for gastric carcinoma(GC).We commend the s...We discuss the findings of Wu et al on the utility of neutrophil-to-lymphocyte ratio,platelet-to-lymphocyte ratio,and systemic immune-inflammatory index as diagnostic markers for gastric carcinoma(GC).We commend the study's contributions to the field and suggest a prospective study to validate these markers'sensitivity and specificity for early GC detection.We also propose developing surveillance protocols that incorporate these markers with other diagnostic methods to enhance clinical decision-making.Furthermore,we highlight the need for a more diverse patient cohort to assess the generalizability of these markers across different ethnic groups and demographic factors.Our suggestions aim to refine the application of these markers in clinical practice and to understand their potential in diverse clinical scenarios.展开更多
Purpose:Currently,different research conclusions exist about the relationship between relational capital and corporate innovation.The research aims to(1)reveal the actual relationship between executive alumni relation...Purpose:Currently,different research conclusions exist about the relationship between relational capital and corporate innovation.The research aims to(1)reveal the actual relationship between executive alumni relations and firm innovation performance,(2)examine the moderating role of executive academic backgrounds,(3)analyze the paths for firms to leverage knowledge spillovers from regional universities to promote firm innovation by their geographic location.Design/methodology/approach:A social network approach is used to construct alumni relationship networks of A-share listed companies in Shanghai and Shenzhen,China.A two-way fixed effects model is used to assess the impact of firms’structural position in executive alumni networks on firms’innovation performance.In addition,the research also delves into the interactions between knowledge spillovers from geographic locations and executives’alumni networks,aiming to elucidate their combined effects on firms’innovation performance.Findings:This paper explores the curvilinear relationship between executive alumni networks’centrality and firm innovation within the Chinese context.It also finds that in the positive effect interval on the right side of the“U-shaped,”the industry with the highest number of occurrences is the high-tech industry.Moreover,it elucidates the moderating influence of executives’academic experience on the alumni networks-innovation nexus,offering a nuanced understanding of these dynamics.Lastly,we provide novel insights into optimizing resource allocation to leverage geographic knowledge spillovers for innovation.Research limitations:The study may not fully represent the broader population of firms,particularly small and medium-sized enterprises(SMEs)or unlisted companies.Future research could expand the sample to include a more diverse range of firms to enhance the generalizability of the findings.Practical implications:Firstly,companies can give due consideration to the alumni resources of executives in their personnel decisions,but they should pay attention to the rational use of resources.Secondly,universities should actively work with companies to promote knowledge transfer and collaboration.Originality/value:The findings help clarify the influence mechanism of firms’innovation performance,providing theoretical support and empirical evidence for firms to drive innovation at the executive alumni relationship network level.展开更多
An optimal fuzzy tracking synthesis for nonlinear discrete-time descriptor systems is discussed through the Parallel Distributed Compensation(PDC)approach and the Proportional-Difference(P-D)feedback framework.Based o...An optimal fuzzy tracking synthesis for nonlinear discrete-time descriptor systems is discussed through the Parallel Distributed Compensation(PDC)approach and the Proportional-Difference(P-D)feedback framework.Based on the Takagi-Sugeno Fuzzy Descriptor Model(T-SFDM),a nonlinear discrete-time descriptor system is represented as several linear fuzzy subsystems,which facilitates the linear P-D feedback technique and streamlines the fuzzy controller design process.Leveraging the P-D feedback fuzzy controller,the closed-loop T-SFDM can be transformed into a standard system that guarantees non-impulsiveness and causality for the nonlinear discrete-time descriptor system.In view of the disturbance problems,a passive performance constraint is incorporated into the fuzzy tracking synthesis to achieve dissipativity of disturbance energy.To achieve a better balance between state and control responses,the H2 performance requirement is considered and a minimization constraint is applied to optimize the H2 index.It is observed that there is a lack of research focusing on both disturbance and control input issues in nonlinear descriptor systems.Extending the Lyapunov theory,a stability analysis method is proposed for the tracking purpose with the combination of the free-weighting matrix to relax the analysis process while complying multiple performance constraints.Finally,two simulation examples are presented to demonstrate the feasibility and applicability of the proposed approach in practical control scenarios for nonlinear descriptor systems.展开更多
The Internet of Things Application(IOTA) is an innovative public blockchain system tailored for the Internet of Things(IoT), focusing on challenges such as micro-payments, concurrency, and scalability. However, its di...The Internet of Things Application(IOTA) is an innovative public blockchain system tailored for the Internet of Things(IoT), focusing on challenges such as micro-payments, concurrency, and scalability. However, its distributed ledger,which utilizes a directed acyclic graph(DAG) structure, is vulnerable to double-spending attacks. To mitigate this risk,we propose a countermeasure employing zero-determinant(ZD) strategies to encourage honest transactions among nodes.First, we analyze the game-theoretic interactions between the IOTA committee and nodes, modeling them as an iterated prisoner's dilemma and deriving the conditions under which this dilemma holds. Next, we explore the conditions under which the IOTA committee can adopt ZD strategies, demonstrating the feasibility of unilaterally controlling node payoffs.Finally, theoretical analysis and experimental validation confirm the effectiveness of the proposed countermeasure, offering a novel game-theoretic solution for enhancing IOTA's security.展开更多
This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with...This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.展开更多
文摘Traditional agricultural irrigation systems waste significant amounts of water and energy due to inefficient scheduling and the absence of real-time monitoring capabilities.This research developed a comprehensive IoT-based smart irrigation control systemto optimize water and energy management in agricultural greenhouses while enhancing crop productivity.The system employs a sophisticated four-layer Internet ofThings(IoT)architecture based on an ESP32 microcontroller,integrated with multiple environmental sensors,including soil moisture,temperature,humidity,and light intensity sensors,for comprehensive environmental monitoring.The system utilizes the Message Queuing Telemetry Transport(MQTT)communication protocol for reliable data transmission and incorporates a Random Forest machine learning algorithm for automated irrigation decision-making processes.The Random Forest model achieved exceptional performance with 99.3%overall accuracy,demonstrating high model reliability.Six operational modules were developed and implemented with three distinct control methods:manual operation,condition-based automatic control,and AI-driven intelligent control systems.A comprehensive one-month comparative analysis demonstrated remarkable improvements across multiple performance metrics:a 50%reduction in both water consumption(from 140 to 70 L/day)and energy usage(from 7.00 to 3.50 kWh/day),a substantial 130%increase in water use efficiency,and a significant 50%decrease in CO_(2) emissions.Furthermore,detailed factor importance analysis revealed soil moisture as the primary decision factor(38.6%),followed by temporal factors(20.3%)and light intensity(18.4%).The system demonstrates exceptional potential for annual energy conservation of 1277.5 kWh and CO_(2) emission reduction of 638.75 kg,contributing substantially to sustainable development goals and advancing smart agriculture technologies.
基金supported under the framework of international cooperation program managed by the National Research Foundation of Korea(Grant Nos.:NRF-2023K2A9A2A06059378 and FY 2023)supported by National Natural Science Foundation of China Program(Grant No.:72032006).
文摘The metaverse has become a very important phenomenon in society because of the emergence of new technologies. The widespread adoption of the metaverse has generated significant discussions about the challenges and opportunities it presents. We invited three panelists to present their personal viewpoints on the metaverse in the 2022 AIS-SIG-ISAP Workshop on Information Systems in Asia-Pacific (ISAP). The discussion indicated that metaverse research is being conducted. Furthermore, it highlighted new research directions and offered research topics related to the advantages or disadvantages of the metaverse. The proposed research topics will offer new insights to academics and practitioners.
文摘The recent rapid development of China’s foreign trade has led to the significant increase in waterway transportation and automated container ports. Automated terminals can significantly improve the loading and unloading efficiency of container terminals. These terminals can also increase the port’s transportation volume while ensuring the quality of cargo loading and unloading, which has become an inevitable trend in the future development of ports. However, the continuous growth of the port’s transportation volume has increased the horizontal transportation pressure on the automated terminal, and the problems of route conflicts and road locks faced by automated guided vehicles (AGV) have become increasingly prominent. Accordingly, this work takes Xiamen Yuanhai automated container terminal as an example. This work focuses on analyzing the interference problem of path conflict in its horizontal transportation AGV scheduling. Results show that path conflict, the most prominent interference factor, will cause AGV scheduling to be unable to execute the original plan. Consequently, the disruption management was used to establish a disturbance recovery model, and the Dijkstra algorithm for combining with time windows is adopted to plan a conflict-free path. Based on the comparison with the rescheduling method, the research obtains that the deviation of the transportation path and the deviation degree of the transportation path under the disruption management method are much lower than those of the rescheduling method. The transportation path deviation degree of the disruption management method is only 5.56%. Meanwhile, the deviation degree of the transportation path under the rescheduling method is 44.44%.
文摘Aiming at the problem that existing models in aspect-level sentiment analysis cannot fully and effectively utilize sentence semantic and syntactic structure information, this paper proposes a graph neural network-based aspect-level sentiment classification model. Self-attention, aspectual word multi-head attention and dependent syntactic relations are fused and the node representations are enhanced with graph convolutional networks to enable the model to fully learn the global semantic and syntactic structural information of sentences. Experimental results show that the model performs well on three public benchmark datasets Rest14, Lap14, and Twitter, improving the accuracy of sentiment classification.
基金Supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_0102)the China Scholarship Council Program(202406190114)。
文摘Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoting high-quality development of new energy in China.This paper constructs an evaluation index system for the development of NEVs and the ecological environment.It uses game theory combining weighting model,particle swarm optimized projection tracking evaluation model,coupling coordination degree model,and machine learning algorithms to calculate and analyze the level of coupling coordination development of NEVs and the ecological environment in China from 2010 to 2021,and identifies the driving factors.The research results show that:(i)From 2010 to 2021,the development index of NEVs in China has steadily increased from 0.085 to 0.634,while the ecological environment level index significantly rose from 0.170 to 0.884,reflecting the continuous development of China in both NEVs and the ecological environment.(ii)From 2010 to 2012,the two systems—new energy vehicle(NEV)development and the ecological environment—were in a period of imbalance and decline.From 2013 to 2016,they underwent a transition period,and from 2017 to 2021,they entered a period of coordinated development showing a trend of benign and continuous improvement.By 2021,they reached a good level of coordination.(iii)Indicators such as the number of patents granted for NEVs,water consumption per unit of GDP,and energy consumption per unit of GDP are the main driving factors affecting the coupling coordination development of NEVs and the ecological environment in China.
基金Supported by the Henan Province Key Research and Development Project(231111211300)the Central Government of Henan Province Guides Local Science and Technology Development Funds(Z20231811005)+2 种基金Henan Province Key Research and Development Project(231111110100)Henan Provincial Outstanding Foreign Scientist Studio(GZS2024006)Henan Provincial Joint Fund for Scientific and Technological Research and Development Plan(Application and Overcoming Technical Barriers)(242103810028)。
文摘The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.
文摘Objective To investigate whether 2,3,5,4'-tetrahydroxystilbene-2-O-β-glucoside(TSG)ameliorated polycystic ovary syndrome(PCOS)-like characteristics by inhibiting inflammation.Methods PCOS models were established by injecting subcutaneously with dehydroepiandrosterone into female Sprague-Dawley rats,followed by receiving intraperitoneal injection of TSG.The granular cells(GCs)KGN were transfected with small interfering RNAs(si-NC and si-CYP19A1).The cells were preincubated with lipopolysaccharide(LPS)and then treated with or without TSG.The estrous cycle was monitored using vaginal exfoliated cells.The morphology of ovarian follicles was analyzed by H&E staining.ELISA was used to analyze estradiol(E2),testosterone(T),follicle stimulating hormone(FSH),luteinizing hormone(LH),IL-6,TNF-α,AGEs,CRP and Omentin-1 levels in serum.Immunohistochemistry was performed to analyze PCNA and CYP19A1 expressions in the GCs of ovaries.Tunel staining was executed to detect the apoptosis of GCs.Quantitative polymerase chain reaction(qPCR)and Western blot were implemented to measure the expression of CYP19A1 in the ovaries and transfected cells.qPCR was used to analyze the expression of IL-6 and TNF-αin the transfected cells treated with LPS and TSG.Results The estrous cycles were restored in TSG group.Compared with model group,the sinus follicles were reduced and corpus luteums were increased in TSG group.TSG group showed increased E2,and decreased T and LH,compared with model group.Pro-inflammatory factors(IL-6,TNF-α,CRP and AGEs)were decreased,and anti-inflammatory factor(Omentin-1)was increased in TSG group compared with those in model group.TSG could partially inhibit decrease of PNCA-positive GCs and increase of Tunel-positive GCs caused by PCOS.The CYP19A1 expression of GCs in TSG group was upregulated compared with model group.The expressions of IL-6 and TNFαin si-CYP19A1 cells were increased compared with si-NC cells.Compared with cells(si-NC and si-CYP19A1)treated without LPS,the expressions of IL-6 and TNF-αcells were increased,and the expression of CYP19A1 was downregulated in LPS-preincubated cells.Compared with cells treated with LPS,the expression of IL-6 and TNF-αwere decreased,and the expression of CYP19A1 was increased in cells treated with LPS and TSG.Compared with si-NC cells treated with LPS and TSG,the expressions of IL-6 and TNF-αcells were increased in the si-CYP19A1 cells treated with LPS and TSG.Conclusion TSG could alleviate PCOS-like characteristics by increasing the expression of CYP19A1 in GCs to inhibit inflammatory response.
基金supported by the Basic Research Program for Young Students(Doctoral Students)of the National Natural Science Foundation of China(#724B2015)。
文摘Purpose:This study examines why papers with high CD indices(measuring research disruptiveness)increasingly show reduced citation impact and investigates whether this represents genuine impact reduction or methodological artifacts.Design/methodology/approach:We analyzed 29 million papers(1950-2016)using Poisson regression to examine relationships between the CD index and citation count,with controls for fields,team size,and reference count.Findings:Papers with high CD indices showed reduced citation impact over time.However,when controlling for increasing reference counts in papers,this relationship reversed,revealing a positive association.Papers with more references exhibit lower CD indices owing to the index’s sensitivity to the reference count,while achieving higher citation counts.Alternative innovation metrics consistently show positive correlations with citation impact.Research limitations:The approach may not adequately capture the reduced citation impact of highly disruptive papers with fewer references.The analysis is limited to journal articles and shows correlation rather than causality.Practical implications:The apparent undervaluation of disruptive research stems from methodological artifacts in the CD index calculation driven by evolving reference patterns.Researchers should control for the reference count when using this metric.Originality/value:This study reveals that bias against disruptive research is specific to the CD index’s calculation methodology,identifying reference behavior as the key factor affecting the relationship between disruption metrics and citation impact.
文摘Hybrid renewable energy systems(HRES)offer cost-effectiveness,low-emission power solutions,and reduced dependence on fossil fuels.However,the renewable energy allocation problem remains challenging due to complex system interactions and multiple operational constraints.This study develops a novel Multi-Neighborhood Enhanced Harris Hawks Optimization(MNEHHO)algorithm to address the allocation of HRES components.The proposed approach integrates key technical parameters,including charge-discharge efficiency,storage device configurations,and renewable energy fraction.We formulate a comprehensive mathematical model that simultaneously minimizes levelized energy costs and pollutant emissions while maintaining system reliability.The MNEHHO algorithm employs multiple neighborhood structures to enhance solution diversity and exploration capabilities.The model’s effectiveness is validated through case studies across four distinct institutional energy demand profiles.Results demonstrate that our approach successfully generates practically feasible HRES configurations while achieving significant reductions in costs and emissions compared to conventional methods.The enhanced search mechanisms of MNEHHO show superior performance in avoiding local optima and achieving consistent solutions.Experimental results demonstrate concrete improvements in solution quality(up to 46% improvement in objective value)and computational efficiency(average coefficient of variance of 24%-27%)across diverse institutional settings.This confirms the robustness and scalability of our method under various operational scenarios,providing a reliable framework for solving renewable energy allocation problems.
文摘This study presents a new approach that advances the algorithm of similarity measures between generalized fuzzy numbers. Following a brief introduction to some properties of the proposed method, a comparative analysis based on 36 sets of generalized fuzzy numbers was performed, in which the degree of similarity of the fuzzy numbers was calculated with the proposed method and seven methods established by previous studies in the literature. The results of the analytical comparison show that the proposed similarity outperforms the existing methods by overcoming their drawbacks and yielding accurate outcomes in all calculations of similarity measures under consideration. Finally, in a numerical example that involves recommending cars to customers based on a nine-member linguistic term set, the proposed similarity measure proves to be competent in addressing fuzzy number recommendation problems.
文摘The paper considers the poor state of the construction industry in UK and ways in which it might improve for all stakeholders.The transition from present state to a desirable future is mapped using the“three horizons”and“four capitals”concepts.Servitisation is suggested as a key innovation for engineering systems in buildings,the dominant lifecycle cost area.Digital twinning facilitates this method of provision and blockchain technology can support its commercialisation,enabling payments for service delivered and keeping safe records.
基金funded by theNational Science and Technology Council of Taiwan under the grant number NSTC 113-2221-E-035-058.
文摘With the rapid expansion of multimedia data,protecting digital information has become increasingly critical.Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multimedia files while enabling full recovery of the original data after extraction.Audio,as a vital medium in communication,entertainment,and information sharing,demands the same level of security as images.However,embedding data in encrypted audio poses unique challenges due to the trade-offs between security,data integrity,and embedding capacity.This paper presents a novel interpolation-based reversible data hiding algorithm for encrypted audio that achieves scalable embedding capacity.By increasing sample density through interpolation,embedding opportunities are significantly enhanced while maintaining encryption throughout the process.The method further integrates multiple most significant bit(multi-MSB)prediction and Huffman coding to optimize compression and embedding efficiency.Experimental results on standard audio datasets demonstrate the proposed algorithm’s ability to embed up to 12.47 bits per sample with over 9.26 bits per sample available for pure embedding capacity,while preserving full reversibility.These results confirm the method’s suitability for secure applications that demand high embedding capacity and perfect reconstruction of original audio.This work advances reversible data hiding in encrypted audio by offering a secure,efficient,and fully reversible data hiding framework.
文摘The primary motivation for this study is the recent growth and increased interest in artificial intelligence(AI).Despite the widespread recognition of its critical importance,a discernible scientific gap persists within the extant scholarly discourse,particularly concerning exhaustive systematic reviews of AI in the aviation industry.This gap spurred a meticulous analysis of 1,213 articles from the Web of Science(WoS)core database for bibliometric knowledge mapping.This analysis highlights China as the primary contributor to publications,with the Nanjing University of Finance and Economics as the leading institution in paper contributions.Lecture Notes in Artificial Intelligence and the IEEE AIAA Digital Avionics System Conference are the leading journals within this domain.This bibliometric research underscores the key focus on air traffic management,human factors,environmental ini-tiatives,training,logistics,flight operations,and safety through co-occurrence and co-citation analyses.A chro-nological examination of keywords reveals a central research trajectory centered on machine learning,models,deep learning,and the impact of automation on human performance in aviation.Burst keyword analysis identifies the leading-edge research on AI within predictive models,unmanned aerial vehicles,object detection,and con-volutional neural networks.The primary objective is to bridge this knowledge gap and gain comprehensive in-sights into AI in the aviation sector.This study delineates the scholarly terrain of AI in aviation using a bibliometric methodology to facilitate this exploration.The results illuminate the current state of research,thereby enhancing academic understanding of developments within this critical domain.Finally,a new con-ceptual framework was constructed based on the primary elements identified in the literature.This framework can assist emerging researchers in identifying the fundamental dimensions of AI in the aviation industry.
文摘We discuss the findings of Wu et al on the utility of neutrophil-to-lymphocyte ratio,platelet-to-lymphocyte ratio,and systemic immune-inflammatory index as diagnostic markers for gastric carcinoma(GC).We commend the study's contributions to the field and suggest a prospective study to validate these markers'sensitivity and specificity for early GC detection.We also propose developing surveillance protocols that incorporate these markers with other diagnostic methods to enhance clinical decision-making.Furthermore,we highlight the need for a more diverse patient cohort to assess the generalizability of these markers across different ethnic groups and demographic factors.Our suggestions aim to refine the application of these markers in clinical practice and to understand their potential in diverse clinical scenarios.
基金supported in part by the National Natural Science Foundation of China under Grant No.72264036,in part by the West Light Foundation of The Chinese Academy of Sciences under Grant No.2020-XBQNXZ-020Xinjiang University of Finance and Economics Postgraduate Innovation Project XJUFE2024K036.
文摘Purpose:Currently,different research conclusions exist about the relationship between relational capital and corporate innovation.The research aims to(1)reveal the actual relationship between executive alumni relations and firm innovation performance,(2)examine the moderating role of executive academic backgrounds,(3)analyze the paths for firms to leverage knowledge spillovers from regional universities to promote firm innovation by their geographic location.Design/methodology/approach:A social network approach is used to construct alumni relationship networks of A-share listed companies in Shanghai and Shenzhen,China.A two-way fixed effects model is used to assess the impact of firms’structural position in executive alumni networks on firms’innovation performance.In addition,the research also delves into the interactions between knowledge spillovers from geographic locations and executives’alumni networks,aiming to elucidate their combined effects on firms’innovation performance.Findings:This paper explores the curvilinear relationship between executive alumni networks’centrality and firm innovation within the Chinese context.It also finds that in the positive effect interval on the right side of the“U-shaped,”the industry with the highest number of occurrences is the high-tech industry.Moreover,it elucidates the moderating influence of executives’academic experience on the alumni networks-innovation nexus,offering a nuanced understanding of these dynamics.Lastly,we provide novel insights into optimizing resource allocation to leverage geographic knowledge spillovers for innovation.Research limitations:The study may not fully represent the broader population of firms,particularly small and medium-sized enterprises(SMEs)or unlisted companies.Future research could expand the sample to include a more diverse range of firms to enhance the generalizability of the findings.Practical implications:Firstly,companies can give due consideration to the alumni resources of executives in their personnel decisions,but they should pay attention to the rational use of resources.Secondly,universities should actively work with companies to promote knowledge transfer and collaboration.Originality/value:The findings help clarify the influence mechanism of firms’innovation performance,providing theoretical support and empirical evidence for firms to drive innovation at the executive alumni relationship network level.
基金founded by the National Science and Technology Council(Taiwan)under contract NSTC113-2221-E-019-032.
文摘An optimal fuzzy tracking synthesis for nonlinear discrete-time descriptor systems is discussed through the Parallel Distributed Compensation(PDC)approach and the Proportional-Difference(P-D)feedback framework.Based on the Takagi-Sugeno Fuzzy Descriptor Model(T-SFDM),a nonlinear discrete-time descriptor system is represented as several linear fuzzy subsystems,which facilitates the linear P-D feedback technique and streamlines the fuzzy controller design process.Leveraging the P-D feedback fuzzy controller,the closed-loop T-SFDM can be transformed into a standard system that guarantees non-impulsiveness and causality for the nonlinear discrete-time descriptor system.In view of the disturbance problems,a passive performance constraint is incorporated into the fuzzy tracking synthesis to achieve dissipativity of disturbance energy.To achieve a better balance between state and control responses,the H2 performance requirement is considered and a minimization constraint is applied to optimize the H2 index.It is observed that there is a lack of research focusing on both disturbance and control input issues in nonlinear descriptor systems.Extending the Lyapunov theory,a stability analysis method is proposed for the tracking purpose with the combination of the free-weighting matrix to relax the analysis process while complying multiple performance constraints.Finally,two simulation examples are presented to demonstrate the feasibility and applicability of the proposed approach in practical control scenarios for nonlinear descriptor systems.
基金Project supported by the Natural Science Foundation of Inner Mongolia, China (Grant No. 2024LHMS06013)Basic Research Funds for Inner Mongolia Autonomous Region’s Directly Affiliated Universities in 2025 (Grant No. NCYWS25019)+2 种基金the Regional Digital Economy and Digital Governance Research Center (Grant No. szzl202401)the Research Project on Education and Teaching Reform at Inner Mongolia University of Finance and Economics (Grant No. JXZD2405)the 2025 High-Quality Research Achievement Cultivation Fund Project of Inner Mongolia University of Finance and Economics (Grant No. GZCG2529)。
文摘The Internet of Things Application(IOTA) is an innovative public blockchain system tailored for the Internet of Things(IoT), focusing on challenges such as micro-payments, concurrency, and scalability. However, its distributed ledger,which utilizes a directed acyclic graph(DAG) structure, is vulnerable to double-spending attacks. To mitigate this risk,we propose a countermeasure employing zero-determinant(ZD) strategies to encourage honest transactions among nodes.First, we analyze the game-theoretic interactions between the IOTA committee and nodes, modeling them as an iterated prisoner's dilemma and deriving the conditions under which this dilemma holds. Next, we explore the conditions under which the IOTA committee can adopt ZD strategies, demonstrating the feasibility of unilaterally controlling node payoffs.Finally, theoretical analysis and experimental validation confirm the effectiveness of the proposed countermeasure, offering a novel game-theoretic solution for enhancing IOTA's security.
基金supported by the National Natural Science Foundation of China(72101025,72271049),the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities,FRF-IDRY-24-024)the Hebei Natural Science Foundation(F2023501011)+1 种基金the Fundamental Research Funds for the Central Universities(FRF-TP-20-073A1)the R&D Program of Beijing Municipal Education Commission(KM202411232015).
文摘This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.
