The complexity of business and information systems(IS)alignment is a growing concern for researchers and practitioners alike.The extant research on alignment architecture fails to consider the human viewpoint,which ma...The complexity of business and information systems(IS)alignment is a growing concern for researchers and practitioners alike.The extant research on alignment architecture fails to consider the human viewpoint,which makes it difficult to embrace emergent complexity.This paper contributes to the extant literature in the following ways.First,we combine an enterprise architecture(EA)framework with a human viewpoint to address alignment issues in the architecture design phase;second,we describe a dynamic alignment model by developing a humancentered meta-model that explains first-and second-order changes and their effects on alignment evolution.This paper provides better support for the theoretical research and the practical application of dynamic alignment.展开更多
Image registration is the overlaying of two images of the same scene taken at different times or by different sensors. It is one of the essential steps in information processing in remote sensing. To attain a highly a...Image registration is the overlaying of two images of the same scene taken at different times or by different sensors. It is one of the essential steps in information processing in remote sensing. To attain a highly accurate, reliable and low computation cost in image registration a suitable and similarity metric and reduction in search data and search space is required. In this paper, the author shows that if the right bin size is chosen, mutual information can be more robust than correlation in the registration of multi-temporal images. The author also compares the sensitivity of mutual information and correlation to Gaussian and multiplicative speckle noise. The author investigates automatic subimage selection as a reduction in search data strategy. The author proposes a measure, called alienability, which shows the ability ofa subimage to provide reliable registration. Alternate subimage selection methods such as using gradient, entropy and variance are also investigated. The author furthermore looks into a search space strategy using a gradient approach to maximize mutual information and show our first results.展开更多
This paper explores the multi-frequency independent channel interference alignment(MFC-IA) system of 3 channels and4 users,and single data stream transmit,i.e.(3×3,1)~4 system.We derive the analytic solution for(...This paper explores the multi-frequency independent channel interference alignment(MFC-IA) system of 3 channels and4 users,and single data stream transmit,i.e.(3×3,1)~4 system.We derive the analytic solution for(3×3,1)~4 MFC-IA system.Based on the analytic solution,an optimization problem is proposed aim at the optimal IA solution.Then based on such a math model,we propose a simulated annealing(SA) algorithm to search optimal IA solution.The simulation results show that the simulated annealing IA algorithm has a better sum rate performance than iterative maximize signal to interference plus noise ratio(Max-SINR) algorithm.This result can be extended to single data stream multi-antenna IA system with 3 antennas and4 users.展开更多
The alignment between information systems （IS） and business strategy along with its implications for perceived IS effectiveness and business performance is an important question, which is rarely studied in China. Ba...The alignment between information systems （IS） and business strategy along with its implications for perceived IS effectiveness and business performance is an important question, which is rarely studied in China. Based on an empirical study, this paper summarized the significance of IS strategic alignment and its impact on business performance. This study also measured business strategy, information system strategy, and information system strategic alignment, built a conceptual model to describe the relationship between these factors, and investigated their implications for information system performance and business performance. A structural equation model was employed to test the conceptual model. Analyses of data gathered in a survey indicate that information system strategic alignment is a better predictor of business performance than business strategy or information system strategy alone, although business strategy can significantly influence business performance.展开更多
Self-attention aggregates similar feature information to enhance the features. However, the attention covers nonface areas in face alignment, which may be disturbed in challenging cases, such as occlusions, and fails ...Self-attention aggregates similar feature information to enhance the features. However, the attention covers nonface areas in face alignment, which may be disturbed in challenging cases, such as occlusions, and fails to predict landmarks. In addition, the learned feature similarity variance is not large enough in the experiment. To this end, we propose structural dependence learning based on self-attention for face alignment (SSFA). It limits the self-attention learning to the facial range and adaptively builds the significant landmark structure dependency. Compared with other state-of-the-art methods, SSFA effectively improves the performance on several standard facial landmark detection benchmarks and adapts more in challenging cases.展开更多
The high-frequency(HF)modeling of induction motors plays a key role in predicting the motor terminal overvoltage and conducted emissions in a motor drive system.In this study,a physics informed neural network-based HF...The high-frequency(HF)modeling of induction motors plays a key role in predicting the motor terminal overvoltage and conducted emissions in a motor drive system.In this study,a physics informed neural network-based HF modeling method,which has the merits of high accuracy,good versatility,and simple parameterization,is proposed.The proposed model of the induction motor consists of a three-phase equivalent circuit with eighteen circuit elements per phase to ensure model accuracy.The per phase circuit structure is symmetric concerning its phase-start and phase-end points.This symmetry enables the proposed model to be applicable for both star-and delta-connected induction motors without having to recalculate the circuit element values when changing the motor connection from star to delta and vice versa.Motor physics knowledge,namely per-phase impedances,are used in the artificial neural network to obtain the values of the circuit elements.The parameterization can be easily implemented within a few minutes using a common personal computer(PC).Case studies verify the effectiveness of the proposed HF modeling method.展开更多
为了解决多模态情感分析中存在异构鸿沟和语义鸿沟,以及模态无法有效融合等问题,提出了一个新的框架,基于跨模态Transformer的语义对齐和信息细化的多模态情感分析模型CM-SAIR(cross-modal semantic alignment and information refineme...为了解决多模态情感分析中存在异构鸿沟和语义鸿沟,以及模态无法有效融合等问题,提出了一个新的框架,基于跨模态Transformer的语义对齐和信息细化的多模态情感分析模型CM-SAIR(cross-modal semantic alignment and information refinement for multi-modal sentiment analysis),可以有效地解决多模态语义不对齐、语义噪声等问题,实现多模态数据更好地交互融合。使用多模态特征嵌入模块(multi-modal feature embedding,MFE)增强视觉和听觉模态的情感信息。通过一个定义良好的模态间语义对齐模块(inter-modal semantic alignment,ISA)进行双模态时间维度的对齐。通过一个模态内的信息细化模块(intra-modal information refinement,IIR)进行情感解析和情感细化。通过多模态门控融合模块(multi-modal gated fusion,MGF)实现模态的有效融合。在流行的多模态情感分析数据集上进行实验,证明了CM-SAIR框架与最先进的基线相比的优势。展开更多
文摘The complexity of business and information systems(IS)alignment is a growing concern for researchers and practitioners alike.The extant research on alignment architecture fails to consider the human viewpoint,which makes it difficult to embrace emergent complexity.This paper contributes to the extant literature in the following ways.First,we combine an enterprise architecture(EA)framework with a human viewpoint to address alignment issues in the architecture design phase;second,we describe a dynamic alignment model by developing a humancentered meta-model that explains first-and second-order changes and their effects on alignment evolution.This paper provides better support for the theoretical research and the practical application of dynamic alignment.
文摘Image registration is the overlaying of two images of the same scene taken at different times or by different sensors. It is one of the essential steps in information processing in remote sensing. To attain a highly accurate, reliable and low computation cost in image registration a suitable and similarity metric and reduction in search data and search space is required. In this paper, the author shows that if the right bin size is chosen, mutual information can be more robust than correlation in the registration of multi-temporal images. The author also compares the sensitivity of mutual information and correlation to Gaussian and multiplicative speckle noise. The author investigates automatic subimage selection as a reduction in search data strategy. The author proposes a measure, called alienability, which shows the ability ofa subimage to provide reliable registration. Alternate subimage selection methods such as using gradient, entropy and variance are also investigated. The author furthermore looks into a search space strategy using a gradient approach to maximize mutual information and show our first results.
基金supported by the 863 Program of China under Grant No.2015AA01A703the Fundamental Research Funds for the Central Universities under Grant No.2014ZD03-02+1 种基金the National Natural Science Foundation of China(NSFC,No.61171104,61571055)fund of State Key Laboratory of Millimeter Wave(SKL of MMW,No.K201501)
文摘This paper explores the multi-frequency independent channel interference alignment(MFC-IA) system of 3 channels and4 users,and single data stream transmit,i.e.(3×3,1)~4 system.We derive the analytic solution for(3×3,1)~4 MFC-IA system.Based on the analytic solution,an optimization problem is proposed aim at the optimal IA solution.Then based on such a math model,we propose a simulated annealing(SA) algorithm to search optimal IA solution.The simulation results show that the simulated annealing IA algorithm has a better sum rate performance than iterative maximize signal to interference plus noise ratio(Max-SINR) algorithm.This result can be extended to single data stream multi-antenna IA system with 3 antennas and4 users.
基金Supported by the National Natural Science Foundation of China (No. 70671001)
文摘The alignment between information systems （IS） and business strategy along with its implications for perceived IS effectiveness and business performance is an important question, which is rarely studied in China. Based on an empirical study, this paper summarized the significance of IS strategic alignment and its impact on business performance. This study also measured business strategy, information system strategy, and information system strategic alignment, built a conceptual model to describe the relationship between these factors, and investigated their implications for information system performance and business performance. A structural equation model was employed to test the conceptual model. Analyses of data gathered in a survey indicate that information system strategic alignment is a better predictor of business performance than business strategy or information system strategy alone, although business strategy can significantly influence business performance.
基金supported by the National Key R&D Program of China(No.2021YFE0205700)the National Natural Science Foundation of China(Nos.62076235,62276260 and 62002356)+1 种基金sponsored by the Zhejiang Lab(No.2021KH0AB07)the Ministry of Education Industry-University Cooperative Education Program(Wei Qiao Venture Group,No.E1425201).
文摘Self-attention aggregates similar feature information to enhance the features. However, the attention covers nonface areas in face alignment, which may be disturbed in challenging cases, such as occlusions, and fails to predict landmarks. In addition, the learned feature similarity variance is not large enough in the experiment. To this end, we propose structural dependence learning based on self-attention for face alignment (SSFA). It limits the self-attention learning to the facial range and adaptively builds the significant landmark structure dependency. Compared with other state-of-the-art methods, SSFA effectively improves the performance on several standard facial landmark detection benchmarks and adapts more in challenging cases.
文摘The high-frequency(HF)modeling of induction motors plays a key role in predicting the motor terminal overvoltage and conducted emissions in a motor drive system.In this study,a physics informed neural network-based HF modeling method,which has the merits of high accuracy,good versatility,and simple parameterization,is proposed.The proposed model of the induction motor consists of a three-phase equivalent circuit with eighteen circuit elements per phase to ensure model accuracy.The per phase circuit structure is symmetric concerning its phase-start and phase-end points.This symmetry enables the proposed model to be applicable for both star-and delta-connected induction motors without having to recalculate the circuit element values when changing the motor connection from star to delta and vice versa.Motor physics knowledge,namely per-phase impedances,are used in the artificial neural network to obtain the values of the circuit elements.The parameterization can be easily implemented within a few minutes using a common personal computer(PC).Case studies verify the effectiveness of the proposed HF modeling method.
文摘为了解决多模态情感分析中存在异构鸿沟和语义鸿沟,以及模态无法有效融合等问题,提出了一个新的框架,基于跨模态Transformer的语义对齐和信息细化的多模态情感分析模型CM-SAIR(cross-modal semantic alignment and information refinement for multi-modal sentiment analysis),可以有效地解决多模态语义不对齐、语义噪声等问题,实现多模态数据更好地交互融合。使用多模态特征嵌入模块(multi-modal feature embedding,MFE)增强视觉和听觉模态的情感信息。通过一个定义良好的模态间语义对齐模块(inter-modal semantic alignment,ISA)进行双模态时间维度的对齐。通过一个模态内的信息细化模块(intra-modal information refinement,IIR)进行情感解析和情感细化。通过多模态门控融合模块(multi-modal gated fusion,MGF)实现模态的有效融合。在流行的多模态情感分析数据集上进行实验,证明了CM-SAIR框架与最先进的基线相比的优势。
