A Hamiltonian system is derived for the plane elasticity problem of two-dimensional dodecagonal quasicrystals by introducing the simple state function. By using symplectic elasticity approach, the analytic solutions o...A Hamiltonian system is derived for the plane elasticity problem of two-dimensional dodecagonal quasicrystals by introducing the simple state function. By using symplectic elasticity approach, the analytic solutions of the phonon and phason displacements are obtained further for the quasicrystal plates. In addition, the effectiveness of the approach is verified by comparison with the data of the finite integral transformation method.展开更多
Scallop culture is an important way of bottom-seeding marine ranching,which is of great significance to improve the current situation of fishery resources.However,there are some problems in site-selection evaluation o...Scallop culture is an important way of bottom-seeding marine ranching,which is of great significance to improve the current situation of fishery resources.However,there are some problems in site-selection evaluation of marine ranching,such as imperfect criteria system,complex structure,untargeted criteria quantification,etc.In addition,no site-selection evaluation method of bottom-seeding culture areas for scallops is available.Therefore,we established a hierarchy structure model according to the analytic hierarchy process(AHP)theory,in which social,physical,chemical,and biological environments are used as main criteria,and marine functional zonation,water depth,current,water temperature,salinity,substrate type,water quality,sediment quality,red tide,phytoplankton,and zooplankton are used as sub-criteria,on which a multi-parameter evaluation system is set up.Meanwhile,the dualism method,assignment method,and membership function method were used to quantify sub-criteria,and a quantitative evaluation for the entire criteria was added,including the evaluation and analysis of two types of unsuitable environmental situations.By overall consideration in scallop yield,quality,and marine ranching construction objectives,the weight of the main criteria could be determined.Five grades in the suitability corresponding to the evaluation result were divided,and the Python language was used to create an evaluation system for efficient calculation and intuitive presentation of the evaluation outcome.Eight marine cases were simulated based on existing survey data,and the results prove that the method is feasible for evaluating and analyzing the site selection of bottom-seeding culture areas for scallops under various environmental situations.The proposed evaluation method can be promoted for the site selection of bottom-seeding marine ranching.This study provided theoretical and methodological references for the site selection evaluation of other types of marine ranching.展开更多
Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professio...Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.展开更多
In regard to unconventional oil reservoirs,the transient dual-porosity and triple-porosity models have been adopted to describe the fluid flow in the complex fracture network.It has been proven to cause inaccurate pro...In regard to unconventional oil reservoirs,the transient dual-porosity and triple-porosity models have been adopted to describe the fluid flow in the complex fracture network.It has been proven to cause inaccurate production evaluations because of the absence of matrix-macrofracture communication.In addition,most of the existing models are solved analytically based on Laplace transform and numerical inversion.Hence,an approximate analytical solution is derived directly in real-time space considering variable matrix blocks and simultaneous matrix depletion.To simplify the derivation,the simultaneous matrix depletion is divided into two parts:one part feeding the macrofractures and the other part feeding the microfractures.Then,a series of partial differential equations(PDEs)describing the transient flow and boundary conditions are constructed and solved analytically by integration.Finally,a relationship between oil rate and production time in real-time space is obtained.The new model is verified against classical analytical models.When the microfracture system and matrix-macrofracture communication is neglected,the result of the new model agrees with those obtained with the dual-porosity and triple-porosity model,respectively.Certainly,the new model also has an excellent agreement with the numerical model.The model is then applied to two actual tight oil wells completed in western Canada sedimentary basin.After identifying the flow regime,the solution suitably matches the field production data,and the model parameters are determined.Through these output parameters,we can accurately forecast the production and even estimate the petrophysical properties.展开更多
Seismic prediction of cracks is of great significance in many disciplines,for which the rock physics model is indispensable.However,up to now,multitudinous analytical models focus primarily on the cracked rock with th...Seismic prediction of cracks is of great significance in many disciplines,for which the rock physics model is indispensable.However,up to now,multitudinous analytical models focus primarily on the cracked rock with the isotropic background,while the explicit model for the cracked rock with the anisotropic background is rarely investigated in spite of such case being often encountered in the earth.Hence,we first studied dependences of the crack opening displacement tensors on the crack dip angle in the coordinate systems formed by symmetry planes of the crack and the background anisotropy,respectively,by forty groups of numerical experiments.Based on the conclusion from the experiments,the analytical solution was derived for the effective elastic properties of the rock with the inclined penny-shaped cracks in the transversely isotropic background.Further,we comprehensively analyzed,according to the developed model,effects of the crack dip angle,background anisotropy,filling fluid and crack density on the effective elastic properties of the cracked rock.The analysis results indicate that the dip angle and background anisotropy can significantly either enhance or weaken the anisotropy degrees of the P-and SH-wave velocities,whereas they have relatively small effects on the SV-wave velocity anisotropy.Moreover,the filling fluid can increase the stiffness coefficients related to the compressional modulus by reducing crack compliance parameters,while its effects on shear coefficients depend on the crack dip angle.The increasing crack density reduces velocities of the dry rock,and decreasing rates of the velocities are affected by the crack dip angle.By comparing with exact numerical results and experimental data,it was demonstrated that the proposed model can achieve high-precision estimations of stiffness coefficients.Moreover,the assumption of the weakly anisotropic background results in the consistency between the proposed model and Hudson's published theory for the orthorhombic rock.展开更多
Based on the Landau-Lifshitz-Gilbert(LLG)equation,the precession relaxation of magnetization is studied when the external field H is parallel to the uniaxial anisotropic field H_(k).The evolution of three-component ma...Based on the Landau-Lifshitz-Gilbert(LLG)equation,the precession relaxation of magnetization is studied when the external field H is parallel to the uniaxial anisotropic field H_(k).The evolution of three-component magnetization is solved analytically under the condition of H=nH_(k)(n=3,1 and 0).It is found that with an increase of H or a decrease of the initial polar angle of magnetization,the relaxation time decreases and the angular frequency of magnetization increases.For comparison,the analytical solution for H_(k)=0 is also given.When the magnetization becomes stable,the angular frequency is proportional to the total effective field acting on the magnetization.The analytical solutions are not only conducive to the understanding of the precession relaxation of magnetization,but also can be used as a standard model to test the numerical calculation of LLG equation.展开更多
The developed system for eye and face detection using Convolutional Neural Networks(CNN)models,followed by eye classification and voice-based assistance,has shown promising potential in enhancing accessibility for ind...The developed system for eye and face detection using Convolutional Neural Networks(CNN)models,followed by eye classification and voice-based assistance,has shown promising potential in enhancing accessibility for individuals with visual impairments.The modular approach implemented in this research allows for a seamless flow of information and assistance between the different components of the system.This research significantly contributes to the field of accessibility technology by integrating computer vision,natural language processing,and voice technologies.By leveraging these advancements,the developed system offers a practical and efficient solution for assisting blind individuals.The modular design ensures flexibility,scalability,and ease of integration with existing assistive technologies.However,it is important to acknowledge that further research and improvements are necessary to enhance the system’s accuracy and usability.Fine-tuning the CNN models and expanding the training dataset can improve eye and face detection as well as eye classification capabilities.Additionally,incorporating real-time responses through sophisticated natural language understanding techniques and expanding the knowledge base of ChatGPT can enhance the system’s ability to provide comprehensive and accurate responses.Overall,this research paves the way for the development of more advanced and robust systems for assisting visually impaired individuals.By leveraging cutting-edge technologies and integrating them into amodular framework,this research contributes to creating a more inclusive and accessible society for individuals with visual impairments.Future work can focus on refining the system,addressing its limitations,and conducting user studies to evaluate its effectiveness and impact in real-world scenarios.展开更多
To date,few models are available in the literature to consider the creep behavior of geosynthetics when predicting the lateral deformation(d)of geosynthetics-reinforced soil(GRS)retaining walls.In this study,a general...To date,few models are available in the literature to consider the creep behavior of geosynthetics when predicting the lateral deformation(d)of geosynthetics-reinforced soil(GRS)retaining walls.In this study,a general hyperbolic creep model was first introduced to describe the long-term deformation of geosynthetics,which is a function of elapsed time and two empirical parameters a and b.The conventional creep tests with three different tensile loads(Pr)were conducted on two uniaxial geogrids to determine their creep behavior,as well as the a-Pr and b-Pr relationships.The test results show that increasing Pr accelerates the development of creep deformation for both geogrids.Meanwhile,a and b respectively show exponential and negatively linear relationships with Pr,which were confirmed by abundant experimental data available in other studies.Based on the above creep model and relationships,an accurate and reliable analytical model was then proposed for predicting the time-dependent d of GRS walls with modular block facing,which was further validated using a relevant numerical investigation from the previous literature.Performance evaluation and comparison of the proposed model with six available prediction models were performed.Then a parametric study was carried out to evaluate the effects of wall height,vertical spacing of geogrids,unit weight and internal friction angle of backfills,and factor of safety against pullout on d at the end of construction and 5 years afterwards.The findings show that the creep effect not only promotes d but also raises the elevation of the maximum d along the wall height.Finally,the limitations and application prospects of the proposed model were discussed and analyzed.展开更多
A versatile analytical method(VAM) for calculating the harmonic components of the magnetomotive force(MMF) generated by diverse armature windings in AC machines has been proposed, and the versatility of this method ha...A versatile analytical method(VAM) for calculating the harmonic components of the magnetomotive force(MMF) generated by diverse armature windings in AC machines has been proposed, and the versatility of this method has been established in early literature. However, its practical applications and significance in advancing the analysis of AC machines need further elaboration. This paper aims to complement VAM by augmenting its theory, offering additional insights into its conclusions, as well as demonstrating its utility in assessing armature windings and its application of calculating torque for permanent magnet synchronous machines(PMSM). This work contributes to advancing the analysis of AC machines and underscores the potential for improved design and performance optimization.展开更多
Big data analytics has been widely adopted by large companies to achieve measurable benefits including increased profitability,customer demand forecasting,cheaper development of products,and improved stock control.Sma...Big data analytics has been widely adopted by large companies to achieve measurable benefits including increased profitability,customer demand forecasting,cheaper development of products,and improved stock control.Small and medium sized enterprises(SMEs)are the backbone of the global economy,comprising of 90%of businesses worldwide.However,only 10%SMEs have adopted big data analytics despite the competitive advantage they could achieve.Previous research has analysed the barriers to adoption and a strategic framework has been developed to help SMEs adopt big data analytics.The framework was converted into a scoring tool which has been applied to multiple case studies of SMEs in the UK.This paper documents the process of evaluating the framework based on the structured feedback from a focus group composed of experienced practitioners.The results of the evaluation are presented with a discussion on the results,and the paper concludes with recommendations to improve the scoring tool based on the proposed framework.The research demonstrates that this positioning tool is beneficial for SMEs to achieve competitive advantages by increasing the application of business intelligence and big data analytics.展开更多
Over the past decade,the swift advancement of metabolomics can be credited to significant progress in technologies such as mass spectrometry,nuclear magnetic resonance,and multivariate statistics.Currently,metabolomic...Over the past decade,the swift advancement of metabolomics can be credited to significant progress in technologies such as mass spectrometry,nuclear magnetic resonance,and multivariate statistics.Currently,metabolomics garners widespread application across diverse fields including drug research and development,early disease detection,toxicology,food and nutrition science,biology,prescription,and chinmedomics,among others.Metabolomics serves as an effective characterization technique,offering insights into physiological process alterations in vivo.These changes may result from various exogenous factors like environmental conditions,stress,medications,as well as endogenous elements including genetic and protein-based influences.The potential scientific outcomes gleaned from these insights have catalyzed the formulation of innovative methods,poised to further broaden the scope of this domain.Today,metabolomics has evolved into a valuable and widely accepted instrument in the life sciences.However,comprehensive reviews focusing on the sample preparation and analytical methodologies employed in metabolomics within the life sciences are surprisingly scant.This review aims to fill that gap,providing an overview of current trends and recent advancements in metabolomics.Particular emphasis is placed on sample preparation,sophisticated analytical techniques,and their applications in life science research.展开更多
This paper presents a game theory-based method for predicting the outcomes of negotiation and group decision-making problems. We propose an extension to the BDM model to address problems where actors’ positions are d...This paper presents a game theory-based method for predicting the outcomes of negotiation and group decision-making problems. We propose an extension to the BDM model to address problems where actors’ positions are distributed over a position spectrum. We generalize the concept of position in the model to incorporate continuous positions for the actors, enabling them to have more flexibility in defining their targets. We explore different possible functions to study the role of the position function and discuss appropriate distance measures for computing the distance between the positions of actors. To validate the proposed extension, we demonstrate the trustworthiness of our model’s performance and interpretation by replicating the results based on data used in earlier studies.展开更多
Objective To identify the critical risks in the process of innovative drug research and development,and to provide reference for improving the efficiency of innovative drug development and risk control in China.Method...Objective To identify the critical risks in the process of innovative drug research and development,and to provide reference for improving the efficiency of innovative drug development and risk control in China.Methods Expert investigation and analytic hierarchy process were used to determine the weights of different risks.Results and Conclusion The research and analysis results showed that the risks at different stages of development had different effects on the success rate of drug development,among which the risk at the drug discovery stage influenced the most.In the drug discovery stage,inappropriate target selection had the greatest impact on the success rate of drug development.The lack of appropriate cell tissue or animal models had the greatest impact on the success rate of drug development from the discovery of a compound to the application for clinical trials.The difference in changes between nonclinical and clinical studies had the greatest impact on the success rate of drug development from early clinical studies to pivotal clinical studies.Incorrect dose selection had the greatest impact on the success rate of drug development from pivotal clinical studies to marketing authorization applications.The biggest impact from the marketing authorization application to the approval stage was inadequate communication with regulators.After investigating the weight of risk factors in the process of innovative drug development based on scientific methods,a new perspective for the risk control of new drug development and improving the research and development efficiency is provided.展开更多
Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodo...Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodologies by analyzing their temporal and spatial development. This study therefore attempts to employ the GIS-based multi-criteria decision analysis and analytical hierarchy process techniques to derive the flood risks management on rice productivity in the Gishari Agricultural Marshland in Rwamagana district, Rwanda. Here, six influencing potential factors to flooding, including river slope, soil texture, Land Use Land Cover through Land Sat 8, rainfall, river distance and Digital Elevation Model are considered for the delineation of flood risk zones. Data acquisition like Landsat 8 images, DEM, land use land cover, slope, and soil class in the study area were considered. Results showed that if the DEM is outdated or inaccurate due to changes in the terrain, such as construction, excavation, or erosion, the predicted flood patterns might not reflect the actual water flow. This could result unexpected flood extents and depths, potentially inundating rice fields that were not previously at risk and this, expectedly explained that the increase 1 m in elevation would reduce the rice productivity by 0.17% due to unplanned flood risks in marshland. It was found that the change in rainfall distribution in Gishari agricultural marshland would also decrease the rice productivity by 0.0018%, which is a sign that rainfall is a major factor of flooding in rice scheme. Rainfall distribution plays a crucial role in flooding analysis and can directly impact rice productivity. Oppositely, another causal factor was Land Use Land Cover (LULC), where the Multivariate Logistic Regression Model Analysis findings showed that the increase of one unit in Land Use Land Cover would increase rice productivity by 0.17% of the total rice productivity from the Gishari Agricultural Marshland. Based on findings from these techniques, the Gishari Agricultural Marshlands having steeped land with grassland is classified into five classes of flooding namely very low, low, moderate, high, and very high which include 430%, 361%, 292%, 223%, and 154%. Government of Rwanda and other implementing agencies and major key actors have to contribute on soil and water conservation strategies to reduce the runoff and soil erosion as major contributors of flooding.展开更多
This pioneering research represents a unique and singular study conducted within the United States, with a specific focus on non-technical graduate students pursuing degrees in business analytics. The primary impetus ...This pioneering research represents a unique and singular study conducted within the United States, with a specific focus on non-technical graduate students pursuing degrees in business analytics. The primary impetus behind this study stems from the escalating demand for data-driven professionals, the diverse academic backgrounds of students, the imperative for adaptable pedagogical methods, the ever-evolving landscape of curriculum designs, and the overarching commitment to fostering educational equity. To investigate these multifaceted dynamics, we employed a data collection method that included the distribution of an online survey on platforms such as LinkedIn. Our survey reached and engaged 74 graduate students actively pursuing degrees in Business Analytics within the United States. This comprehensive research is the first and only one of its kind conducted in this context, and it serves as a vanguard exploration into the challenges and influences that shape the learning journey of Python among non-technical graduate Business Analytics students. The analytical insights derived from this research underscore the pivotal role of hands-on learning strategies, exemplified by practice exercises and assignments. Moreover, the study highlights the positive and constructive influence of collaboration and peer support in the process of learning Python. These invaluable findings significantly augment the existing body of knowledge in the field of business analytics. Furthermore, they offer an essential resource for educators and institutions seeking to optimize the educational experiences of non-technical students as they acquire essential Python skills.展开更多
Similarity has been playing an important role in computer science,artificial intelligence(AI)and data science.However,similarity intelligence has been ignored in these disciplines.Similarity intelligence is a process ...Similarity has been playing an important role in computer science,artificial intelligence(AI)and data science.However,similarity intelligence has been ignored in these disciplines.Similarity intelligence is a process of discovering intelligence through similarity.This article will explore similarity intelligence,similarity-based reasoning,similarity computing and analytics.More specifically,this article looks at the similarity as an intelligence and its impact on a few areas in the real world.It explores similarity intelligence accompanying experience-based intelligence,knowledge-based intelligence,and data-based intelligence to play an important role in computer science,AI,and data science.This article explores similarity-based reasoning(SBR)and proposes three similarity-based inference rules.It then examines similarity computing and analytics,and a multiagent SBR system.The main contributions of this article are:1)Similarity intelligence is discovered from experience-based intelligence consisting of data-based intelligence and knowledge-based intelligence.2)Similarity-based reasoning,computing and analytics can be used to create similarity intelligence.The proposed approach will facilitate research and development of similarity intelligence,similarity computing and analytics,machine learning and case-based reasoning.展开更多
The whole-beach quality assessment is the basis of building and preserving beautiful beaches.The beach quality assessment index system and assessment standard have been established based on the attributes of beaches(i...The whole-beach quality assessment is the basis of building and preserving beautiful beaches.The beach quality assessment index system and assessment standard have been established based on the attributes of beaches(including the width,slope,landform,and types),sorting coefficient,and softness degree of surface sediment.The assessment weight of each index for quality evaluation was analyzed using the analytic hierarchy process,and comprehensive scores of selected beach profiles were calculated in accordance with the light assessment standard.A beach quality evaluation model based on index weight and scores was established in this paper.The factors of 12 profiles of Yangkou Beach in Qingdao City were surveyed to carry out a quality assessment,and the comprehensive scores of each profile were calculated in accordance with the evaluation model.The results showed that the quality of Yangkou Beach can be divided into four ratings:excellent,good,medium,and poor.The excellent-quality area includes a wide and flat dry beach zone and soft,flat,and clean intertidal and subtidal zones covered with well-sorted fine sand,and leisure sports,such as volleyball,running,and swimming,are suitable for tourists.The good-quality area features a slightly narrow and dry beach zone,moderately soft and uneven intertidal and subtidal zones covered with fine sand and a small tidal gully,and a small amount of foreign matter;leisure sports,such as walking and running,are suitable for tourists.This study recommends the building of fixed drainage ditches or underground culverts to reduce the tidal gully.The medium-quality area consisted of a narrow and dry beach zone,moderately soft and uneven intertidal and subtidal zones covered by poorly sorted medium sand,a tide ditch,and a small amount of foreign matter.In this area,walking is suitable for tourists.Sand should be supplemented in the intertidal zone.The poor-quality area contained a very narrow and dry beach zone covered with poor-sorted gravel,a very chaotic intertidal zone with a considerable amount of foreign matters,such as bricks and rocks,wide tidal ditches,and an uneven subtidal zone with some reefs;leisure sports are unsuitable here.Thus,foreign matter and reefs should be removed,and the dry beach zone should be supplemented with sand.Therefore,the beach quality assessment is a very useful tool for building beautiful beaches.展开更多
Pseudocapacitive materials that store charges via reversible surface or near-surface faradaic reactions are capable of overcoming the capacity limitations of electrical double-layer capacitors.Revealing the structure...Pseudocapacitive materials that store charges via reversible surface or near-surface faradaic reactions are capable of overcoming the capacity limitations of electrical double-layer capacitors.Revealing the structure–activity relationship between the microstructural features of pseudocapacitive materials and their electrochemical performance on the atomic scale is the key to build high-performance capacitor-type devices containing ideal pseudocapacitance effect.Currently,the high brightness(flux),and spectral and coherent nature of synchrotron X-ray analytical techniques make it a powerful tool for probing the structure–property relationship of pseudocapacitive materials.Herein,we report a comprehensive and systematic review of four typical characterization techniques(synchrotron X-ray diffraction,pair distribution function[PDF]analysis,soft X-ray absorption spectroscopy,and hard X-ray absorption spectroscopy)for the study of pseudocapacitance mechanisms.In addition,we offered significant insights for understanding and identifying pseudocapacitance mechanisms(surface redox pseudocapacitance,intercalation pseudocapacitance,and the extrinsic pseudocapacitance phenomenon in battery materials)by combining in situ hard XAS and electrochemical analyses.Finally,a perspective for further depth of understanding into the pseudocapacitance mechanism using synchrotron X-ray analytical techniques is proposed.展开更多
The adoption of Internet of Things(IoT)sensing devices is growing rapidly due to their ability to provide realtime services.However,it is constrained by limited data storage and processing power.It offloads its massiv...The adoption of Internet of Things(IoT)sensing devices is growing rapidly due to their ability to provide realtime services.However,it is constrained by limited data storage and processing power.It offloads its massive data stream to edge devices and the cloud for adequate storage and processing.This further leads to the challenges of data outliers,data redundancies,and cloud resource load balancing that would affect the execution and outcome of data streams.This paper presents a review of existing analytics algorithms deployed on IoT-enabled edge cloud infrastructure that resolved the challenges of data outliers,data redundancies,and cloud resource load balancing.The review highlights the problems solved,the results,the weaknesses of the existing algorithms,and the physical and virtual cloud storage servers for resource load balancing.In addition,it discusses the adoption of network protocols that govern the interaction between the three-layer architecture of IoT sensing devices enabled edge cloud and its prevailing challenges.A total of 72 algorithms covering the categories of classification,regression,clustering,deep learning,and optimization have been reviewed.The classification approach has been widely adopted to solve the problem of redundant data,while clustering and optimization approaches are more used for outlier detection and cloud resource allocation.展开更多
In this work,we study the linearized Landau equation with soft potentials and show that the smooth solution to the Cauchy problem with initial datum in L^(2)(ℝ^(3))enjoys an analytic regularization effect,and that the...In this work,we study the linearized Landau equation with soft potentials and show that the smooth solution to the Cauchy problem with initial datum in L^(2)(ℝ^(3))enjoys an analytic regularization effect,and that the evolution of the analytic radius is the same as the heat equations.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant Nos.12261064 and 11861048)the Natural Science Foundation of Inner Mongolia,China (Grant Nos.2021MS01004 and 2022QN01008)the High-level Talents Scientific Research Start-up Foundation of Inner Mongolia University (Grant No.10000-21311201/165)。
文摘A Hamiltonian system is derived for the plane elasticity problem of two-dimensional dodecagonal quasicrystals by introducing the simple state function. By using symplectic elasticity approach, the analytic solutions of the phonon and phason displacements are obtained further for the quasicrystal plates. In addition, the effectiveness of the approach is verified by comparison with the data of the finite integral transformation method.
基金Supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB 42010203)the National Natural Science Foundation of China(No.42176090)。
文摘Scallop culture is an important way of bottom-seeding marine ranching,which is of great significance to improve the current situation of fishery resources.However,there are some problems in site-selection evaluation of marine ranching,such as imperfect criteria system,complex structure,untargeted criteria quantification,etc.In addition,no site-selection evaluation method of bottom-seeding culture areas for scallops is available.Therefore,we established a hierarchy structure model according to the analytic hierarchy process(AHP)theory,in which social,physical,chemical,and biological environments are used as main criteria,and marine functional zonation,water depth,current,water temperature,salinity,substrate type,water quality,sediment quality,red tide,phytoplankton,and zooplankton are used as sub-criteria,on which a multi-parameter evaluation system is set up.Meanwhile,the dualism method,assignment method,and membership function method were used to quantify sub-criteria,and a quantitative evaluation for the entire criteria was added,including the evaluation and analysis of two types of unsuitable environmental situations.By overall consideration in scallop yield,quality,and marine ranching construction objectives,the weight of the main criteria could be determined.Five grades in the suitability corresponding to the evaluation result were divided,and the Python language was used to create an evaluation system for efficient calculation and intuitive presentation of the evaluation outcome.Eight marine cases were simulated based on existing survey data,and the results prove that the method is feasible for evaluating and analyzing the site selection of bottom-seeding culture areas for scallops under various environmental situations.The proposed evaluation method can be promoted for the site selection of bottom-seeding marine ranching.This study provided theoretical and methodological references for the site selection evaluation of other types of marine ranching.
基金supported by the National Key Research,Development Program of China (2020AAA0103404)the Beijing Nova Program (20220484077)the National Natural Science Foundation of China (62073323)。
文摘Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.
基金This study was supported by Basic Research Project from Jiangmen Science and Technology Bureau(Grant No.2220002000356)China University of Petroleum(Beijing)(Grand No.2462023BJRC007)The Guangdong Basic and Applied Basic Research Foundation(No.2022A1515110376).
文摘In regard to unconventional oil reservoirs,the transient dual-porosity and triple-porosity models have been adopted to describe the fluid flow in the complex fracture network.It has been proven to cause inaccurate production evaluations because of the absence of matrix-macrofracture communication.In addition,most of the existing models are solved analytically based on Laplace transform and numerical inversion.Hence,an approximate analytical solution is derived directly in real-time space considering variable matrix blocks and simultaneous matrix depletion.To simplify the derivation,the simultaneous matrix depletion is divided into two parts:one part feeding the macrofractures and the other part feeding the microfractures.Then,a series of partial differential equations(PDEs)describing the transient flow and boundary conditions are constructed and solved analytically by integration.Finally,a relationship between oil rate and production time in real-time space is obtained.The new model is verified against classical analytical models.When the microfracture system and matrix-macrofracture communication is neglected,the result of the new model agrees with those obtained with the dual-porosity and triple-porosity model,respectively.Certainly,the new model also has an excellent agreement with the numerical model.The model is then applied to two actual tight oil wells completed in western Canada sedimentary basin.After identifying the flow regime,the solution suitably matches the field production data,and the model parameters are determined.Through these output parameters,we can accurately forecast the production and even estimate the petrophysical properties.
基金We would like to acknowledge all the reviewers and editors and the sponsorship of National Natural Science Foundation of China(42030103)the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(2021QNLM020001-6)the Laoshan National Laboratory of Science and Technology Foundation(LSKJ202203400).
文摘Seismic prediction of cracks is of great significance in many disciplines,for which the rock physics model is indispensable.However,up to now,multitudinous analytical models focus primarily on the cracked rock with the isotropic background,while the explicit model for the cracked rock with the anisotropic background is rarely investigated in spite of such case being often encountered in the earth.Hence,we first studied dependences of the crack opening displacement tensors on the crack dip angle in the coordinate systems formed by symmetry planes of the crack and the background anisotropy,respectively,by forty groups of numerical experiments.Based on the conclusion from the experiments,the analytical solution was derived for the effective elastic properties of the rock with the inclined penny-shaped cracks in the transversely isotropic background.Further,we comprehensively analyzed,according to the developed model,effects of the crack dip angle,background anisotropy,filling fluid and crack density on the effective elastic properties of the cracked rock.The analysis results indicate that the dip angle and background anisotropy can significantly either enhance or weaken the anisotropy degrees of the P-and SH-wave velocities,whereas they have relatively small effects on the SV-wave velocity anisotropy.Moreover,the filling fluid can increase the stiffness coefficients related to the compressional modulus by reducing crack compliance parameters,while its effects on shear coefficients depend on the crack dip angle.The increasing crack density reduces velocities of the dry rock,and decreasing rates of the velocities are affected by the crack dip angle.By comparing with exact numerical results and experimental data,it was demonstrated that the proposed model can achieve high-precision estimations of stiffness coefficients.Moreover,the assumption of the weakly anisotropic background results in the consistency between the proposed model and Hudson's published theory for the orthorhombic rock.
基金Project supported by the National Key R&D Program of China (Grant No.2021YFB3501300)the National Natural Science Foundation of China (Grant Nos.91963201 and 12174163)the 111 Project (Grant No.B20063)。
文摘Based on the Landau-Lifshitz-Gilbert(LLG)equation,the precession relaxation of magnetization is studied when the external field H is parallel to the uniaxial anisotropic field H_(k).The evolution of three-component magnetization is solved analytically under the condition of H=nH_(k)(n=3,1 and 0).It is found that with an increase of H or a decrease of the initial polar angle of magnetization,the relaxation time decreases and the angular frequency of magnetization increases.For comparison,the analytical solution for H_(k)=0 is also given.When the magnetization becomes stable,the angular frequency is proportional to the total effective field acting on the magnetization.The analytical solutions are not only conducive to the understanding of the precession relaxation of magnetization,but also can be used as a standard model to test the numerical calculation of LLG equation.
文摘The developed system for eye and face detection using Convolutional Neural Networks(CNN)models,followed by eye classification and voice-based assistance,has shown promising potential in enhancing accessibility for individuals with visual impairments.The modular approach implemented in this research allows for a seamless flow of information and assistance between the different components of the system.This research significantly contributes to the field of accessibility technology by integrating computer vision,natural language processing,and voice technologies.By leveraging these advancements,the developed system offers a practical and efficient solution for assisting blind individuals.The modular design ensures flexibility,scalability,and ease of integration with existing assistive technologies.However,it is important to acknowledge that further research and improvements are necessary to enhance the system’s accuracy and usability.Fine-tuning the CNN models and expanding the training dataset can improve eye and face detection as well as eye classification capabilities.Additionally,incorporating real-time responses through sophisticated natural language understanding techniques and expanding the knowledge base of ChatGPT can enhance the system’s ability to provide comprehensive and accurate responses.Overall,this research paves the way for the development of more advanced and robust systems for assisting visually impaired individuals.By leveraging cutting-edge technologies and integrating them into amodular framework,this research contributes to creating a more inclusive and accessible society for individuals with visual impairments.Future work can focus on refining the system,addressing its limitations,and conducting user studies to evaluate its effectiveness and impact in real-world scenarios.
基金This research work was financially supported by the National Natural Science Foundation of China(Grant Nos.52078182 and 41877255)the Tianjin Municipal Natural Science Foundation(Grant No.20JCYBJC00630).Their financial support is gratefully acknowledged.
文摘To date,few models are available in the literature to consider the creep behavior of geosynthetics when predicting the lateral deformation(d)of geosynthetics-reinforced soil(GRS)retaining walls.In this study,a general hyperbolic creep model was first introduced to describe the long-term deformation of geosynthetics,which is a function of elapsed time and two empirical parameters a and b.The conventional creep tests with three different tensile loads(Pr)were conducted on two uniaxial geogrids to determine their creep behavior,as well as the a-Pr and b-Pr relationships.The test results show that increasing Pr accelerates the development of creep deformation for both geogrids.Meanwhile,a and b respectively show exponential and negatively linear relationships with Pr,which were confirmed by abundant experimental data available in other studies.Based on the above creep model and relationships,an accurate and reliable analytical model was then proposed for predicting the time-dependent d of GRS walls with modular block facing,which was further validated using a relevant numerical investigation from the previous literature.Performance evaluation and comparison of the proposed model with six available prediction models were performed.Then a parametric study was carried out to evaluate the effects of wall height,vertical spacing of geogrids,unit weight and internal friction angle of backfills,and factor of safety against pullout on d at the end of construction and 5 years afterwards.The findings show that the creep effect not only promotes d but also raises the elevation of the maximum d along the wall height.Finally,the limitations and application prospects of the proposed model were discussed and analyzed.
基金supported by the Natural Science Foundation of China under Grant U22A20214 and Grant 51837010。
文摘A versatile analytical method(VAM) for calculating the harmonic components of the magnetomotive force(MMF) generated by diverse armature windings in AC machines has been proposed, and the versatility of this method has been established in early literature. However, its practical applications and significance in advancing the analysis of AC machines need further elaboration. This paper aims to complement VAM by augmenting its theory, offering additional insights into its conclusions, as well as demonstrating its utility in assessing armature windings and its application of calculating torque for permanent magnet synchronous machines(PMSM). This work contributes to advancing the analysis of AC machines and underscores the potential for improved design and performance optimization.
文摘Big data analytics has been widely adopted by large companies to achieve measurable benefits including increased profitability,customer demand forecasting,cheaper development of products,and improved stock control.Small and medium sized enterprises(SMEs)are the backbone of the global economy,comprising of 90%of businesses worldwide.However,only 10%SMEs have adopted big data analytics despite the competitive advantage they could achieve.Previous research has analysed the barriers to adoption and a strategic framework has been developed to help SMEs adopt big data analytics.The framework was converted into a scoring tool which has been applied to multiple case studies of SMEs in the UK.This paper documents the process of evaluating the framework based on the structured feedback from a focus group composed of experienced practitioners.The results of the evaluation are presented with a discussion on the results,and the paper concludes with recommendations to improve the scoring tool based on the proposed framework.The research demonstrates that this positioning tool is beneficial for SMEs to achieve competitive advantages by increasing the application of business intelligence and big data analytics.
基金supported by the Science Foundation of Heilongjiang Administration of Traditional Chinese Medicine(No.2018-21).
文摘Over the past decade,the swift advancement of metabolomics can be credited to significant progress in technologies such as mass spectrometry,nuclear magnetic resonance,and multivariate statistics.Currently,metabolomics garners widespread application across diverse fields including drug research and development,early disease detection,toxicology,food and nutrition science,biology,prescription,and chinmedomics,among others.Metabolomics serves as an effective characterization technique,offering insights into physiological process alterations in vivo.These changes may result from various exogenous factors like environmental conditions,stress,medications,as well as endogenous elements including genetic and protein-based influences.The potential scientific outcomes gleaned from these insights have catalyzed the formulation of innovative methods,poised to further broaden the scope of this domain.Today,metabolomics has evolved into a valuable and widely accepted instrument in the life sciences.However,comprehensive reviews focusing on the sample preparation and analytical methodologies employed in metabolomics within the life sciences are surprisingly scant.This review aims to fill that gap,providing an overview of current trends and recent advancements in metabolomics.Particular emphasis is placed on sample preparation,sophisticated analytical techniques,and their applications in life science research.
文摘This paper presents a game theory-based method for predicting the outcomes of negotiation and group decision-making problems. We propose an extension to the BDM model to address problems where actors’ positions are distributed over a position spectrum. We generalize the concept of position in the model to incorporate continuous positions for the actors, enabling them to have more flexibility in defining their targets. We explore different possible functions to study the role of the position function and discuss appropriate distance measures for computing the distance between the positions of actors. To validate the proposed extension, we demonstrate the trustworthiness of our model’s performance and interpretation by replicating the results based on data used in earlier studies.
文摘Objective To identify the critical risks in the process of innovative drug research and development,and to provide reference for improving the efficiency of innovative drug development and risk control in China.Methods Expert investigation and analytic hierarchy process were used to determine the weights of different risks.Results and Conclusion The research and analysis results showed that the risks at different stages of development had different effects on the success rate of drug development,among which the risk at the drug discovery stage influenced the most.In the drug discovery stage,inappropriate target selection had the greatest impact on the success rate of drug development.The lack of appropriate cell tissue or animal models had the greatest impact on the success rate of drug development from the discovery of a compound to the application for clinical trials.The difference in changes between nonclinical and clinical studies had the greatest impact on the success rate of drug development from early clinical studies to pivotal clinical studies.Incorrect dose selection had the greatest impact on the success rate of drug development from pivotal clinical studies to marketing authorization applications.The biggest impact from the marketing authorization application to the approval stage was inadequate communication with regulators.After investigating the weight of risk factors in the process of innovative drug development based on scientific methods,a new perspective for the risk control of new drug development and improving the research and development efficiency is provided.
文摘Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodologies by analyzing their temporal and spatial development. This study therefore attempts to employ the GIS-based multi-criteria decision analysis and analytical hierarchy process techniques to derive the flood risks management on rice productivity in the Gishari Agricultural Marshland in Rwamagana district, Rwanda. Here, six influencing potential factors to flooding, including river slope, soil texture, Land Use Land Cover through Land Sat 8, rainfall, river distance and Digital Elevation Model are considered for the delineation of flood risk zones. Data acquisition like Landsat 8 images, DEM, land use land cover, slope, and soil class in the study area were considered. Results showed that if the DEM is outdated or inaccurate due to changes in the terrain, such as construction, excavation, or erosion, the predicted flood patterns might not reflect the actual water flow. This could result unexpected flood extents and depths, potentially inundating rice fields that were not previously at risk and this, expectedly explained that the increase 1 m in elevation would reduce the rice productivity by 0.17% due to unplanned flood risks in marshland. It was found that the change in rainfall distribution in Gishari agricultural marshland would also decrease the rice productivity by 0.0018%, which is a sign that rainfall is a major factor of flooding in rice scheme. Rainfall distribution plays a crucial role in flooding analysis and can directly impact rice productivity. Oppositely, another causal factor was Land Use Land Cover (LULC), where the Multivariate Logistic Regression Model Analysis findings showed that the increase of one unit in Land Use Land Cover would increase rice productivity by 0.17% of the total rice productivity from the Gishari Agricultural Marshland. Based on findings from these techniques, the Gishari Agricultural Marshlands having steeped land with grassland is classified into five classes of flooding namely very low, low, moderate, high, and very high which include 430%, 361%, 292%, 223%, and 154%. Government of Rwanda and other implementing agencies and major key actors have to contribute on soil and water conservation strategies to reduce the runoff and soil erosion as major contributors of flooding.
文摘This pioneering research represents a unique and singular study conducted within the United States, with a specific focus on non-technical graduate students pursuing degrees in business analytics. The primary impetus behind this study stems from the escalating demand for data-driven professionals, the diverse academic backgrounds of students, the imperative for adaptable pedagogical methods, the ever-evolving landscape of curriculum designs, and the overarching commitment to fostering educational equity. To investigate these multifaceted dynamics, we employed a data collection method that included the distribution of an online survey on platforms such as LinkedIn. Our survey reached and engaged 74 graduate students actively pursuing degrees in Business Analytics within the United States. This comprehensive research is the first and only one of its kind conducted in this context, and it serves as a vanguard exploration into the challenges and influences that shape the learning journey of Python among non-technical graduate Business Analytics students. The analytical insights derived from this research underscore the pivotal role of hands-on learning strategies, exemplified by practice exercises and assignments. Moreover, the study highlights the positive and constructive influence of collaboration and peer support in the process of learning Python. These invaluable findings significantly augment the existing body of knowledge in the field of business analytics. Furthermore, they offer an essential resource for educators and institutions seeking to optimize the educational experiences of non-technical students as they acquire essential Python skills.
文摘Similarity has been playing an important role in computer science,artificial intelligence(AI)and data science.However,similarity intelligence has been ignored in these disciplines.Similarity intelligence is a process of discovering intelligence through similarity.This article will explore similarity intelligence,similarity-based reasoning,similarity computing and analytics.More specifically,this article looks at the similarity as an intelligence and its impact on a few areas in the real world.It explores similarity intelligence accompanying experience-based intelligence,knowledge-based intelligence,and data-based intelligence to play an important role in computer science,AI,and data science.This article explores similarity-based reasoning(SBR)and proposes three similarity-based inference rules.It then examines similarity computing and analytics,and a multiagent SBR system.The main contributions of this article are:1)Similarity intelligence is discovered from experience-based intelligence consisting of data-based intelligence and knowledge-based intelligence.2)Similarity-based reasoning,computing and analytics can be used to create similarity intelligence.The proposed approach will facilitate research and development of similarity intelligence,similarity computing and analytics,machine learning and case-based reasoning.
基金supported by the Intercollegiate Cooperation Plan of Innovation and Entrepreneurship Training Program for College Students of Beijing City(No.202211012).
文摘The whole-beach quality assessment is the basis of building and preserving beautiful beaches.The beach quality assessment index system and assessment standard have been established based on the attributes of beaches(including the width,slope,landform,and types),sorting coefficient,and softness degree of surface sediment.The assessment weight of each index for quality evaluation was analyzed using the analytic hierarchy process,and comprehensive scores of selected beach profiles were calculated in accordance with the light assessment standard.A beach quality evaluation model based on index weight and scores was established in this paper.The factors of 12 profiles of Yangkou Beach in Qingdao City were surveyed to carry out a quality assessment,and the comprehensive scores of each profile were calculated in accordance with the evaluation model.The results showed that the quality of Yangkou Beach can be divided into four ratings:excellent,good,medium,and poor.The excellent-quality area includes a wide and flat dry beach zone and soft,flat,and clean intertidal and subtidal zones covered with well-sorted fine sand,and leisure sports,such as volleyball,running,and swimming,are suitable for tourists.The good-quality area features a slightly narrow and dry beach zone,moderately soft and uneven intertidal and subtidal zones covered with fine sand and a small tidal gully,and a small amount of foreign matter;leisure sports,such as walking and running,are suitable for tourists.This study recommends the building of fixed drainage ditches or underground culverts to reduce the tidal gully.The medium-quality area consisted of a narrow and dry beach zone,moderately soft and uneven intertidal and subtidal zones covered by poorly sorted medium sand,a tide ditch,and a small amount of foreign matter.In this area,walking is suitable for tourists.Sand should be supplemented in the intertidal zone.The poor-quality area contained a very narrow and dry beach zone covered with poor-sorted gravel,a very chaotic intertidal zone with a considerable amount of foreign matters,such as bricks and rocks,wide tidal ditches,and an uneven subtidal zone with some reefs;leisure sports are unsuitable here.Thus,foreign matter and reefs should be removed,and the dry beach zone should be supplemented with sand.Therefore,the beach quality assessment is a very useful tool for building beautiful beaches.
基金financialy supported by National Key R&D Program of China(2022YFB2402600)the National Natural Science Foundation of China(22279166)+1 种基金the Research Start-up Funds from Sun Yat-Sen University(200306)the Fundamental Research Funds for the Central Universities,Sun Yat-Sen University(22qntd0101 and 22dfx01)
文摘Pseudocapacitive materials that store charges via reversible surface or near-surface faradaic reactions are capable of overcoming the capacity limitations of electrical double-layer capacitors.Revealing the structure–activity relationship between the microstructural features of pseudocapacitive materials and their electrochemical performance on the atomic scale is the key to build high-performance capacitor-type devices containing ideal pseudocapacitance effect.Currently,the high brightness(flux),and spectral and coherent nature of synchrotron X-ray analytical techniques make it a powerful tool for probing the structure–property relationship of pseudocapacitive materials.Herein,we report a comprehensive and systematic review of four typical characterization techniques(synchrotron X-ray diffraction,pair distribution function[PDF]analysis,soft X-ray absorption spectroscopy,and hard X-ray absorption spectroscopy)for the study of pseudocapacitance mechanisms.In addition,we offered significant insights for understanding and identifying pseudocapacitance mechanisms(surface redox pseudocapacitance,intercalation pseudocapacitance,and the extrinsic pseudocapacitance phenomenon in battery materials)by combining in situ hard XAS and electrochemical analyses.Finally,a perspective for further depth of understanding into the pseudocapacitance mechanism using synchrotron X-ray analytical techniques is proposed.
文摘The adoption of Internet of Things(IoT)sensing devices is growing rapidly due to their ability to provide realtime services.However,it is constrained by limited data storage and processing power.It offloads its massive data stream to edge devices and the cloud for adequate storage and processing.This further leads to the challenges of data outliers,data redundancies,and cloud resource load balancing that would affect the execution and outcome of data streams.This paper presents a review of existing analytics algorithms deployed on IoT-enabled edge cloud infrastructure that resolved the challenges of data outliers,data redundancies,and cloud resource load balancing.The review highlights the problems solved,the results,the weaknesses of the existing algorithms,and the physical and virtual cloud storage servers for resource load balancing.In addition,it discusses the adoption of network protocols that govern the interaction between the three-layer architecture of IoT sensing devices enabled edge cloud and its prevailing challenges.A total of 72 algorithms covering the categories of classification,regression,clustering,deep learning,and optimization have been reviewed.The classification approach has been widely adopted to solve the problem of redundant data,while clustering and optimization approaches are more used for outlier detection and cloud resource allocation.
基金supported by the Natural Science Foundation of Hubei Province,China (2022CFB444)the Key Laboratory of Mathematical Modelling and High Performance Computing of Air Vehicles (NUAA)+1 种基金supported by the NSFC (12031006)the Fundamental Research Funds for the Central Universities of China.
文摘In this work,we study the linearized Landau equation with soft potentials and show that the smooth solution to the Cauchy problem with initial datum in L^(2)(ℝ^(3))enjoys an analytic regularization effect,and that the evolution of the analytic radius is the same as the heat equations.
