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Impact of IT Capability on Inventory management: An Empirical Study 8

Impact of IT Capability on Inventory Management: An Empirica...

8th International Conference on Information Technology and Quantitative management (ITQM) - Developing Global Digital Economy after COVID-19

作者： Tian, Xin Wang, Haoqing Chinese Acad Sci Res Ctr Fictitious Econ & Data Sci Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Econ & Management Beijing 100190 Peoples R China Chinese Acad Sci Key Lab Big Data Min & Knowledge Management Beijing 100190 Peoples R China

Despite the widespread adoption of technology in inventory management, empirical research that examines the effect of these technologies is scarce. Does IT capability really have a positive effect on the inventory management? This paper empirically studies the usage of information technology by the definition of IT capability. Our unique panel data set allows us to explore the relationship between technology usage and inventory management. Our results show that IT capability has a positive effect on the inventory strategy and inventory operation process, and has a negative effect on the out-of-stock level. Our research demonstrates the superiority of the usage of technology. (C) 2021 The Authors. Published by Elsevier B.V.

关键词： intelligent warehousing business intelligence inventory management logistics

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Statistical QoS Provisioning for Underwater Magnetic Induction Communication

arXiv

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arXiv 2025年

作者： Li, Zhichao Wang, Jianyu Cheng, Wenchi Fang, Yudong State Key Laboratory of Integrated Services Networks Xidian University Xi’an China Ministry of Emergency Management Big Data Center Beijing China

Magnetic induction (MI) communication, with stable channel conditions and small antenna size, is considered as a promising solution for underwater communication network. However, the narrowband nature of the MI link can cause significant delays in the network. To comprehensively ensure the timeliness and effectiveness of the MI network, in this paper we introduce a statistical quality of service (QoS) framework for MI communication, aiming to maximize the achievable rate while provisioning delay and queue-length requirements. Specifically, we employ effective capacity theory to model underwater MI communication. Based on convex optimization theory, we propose a current control strategy that maximizes the effective capacity under the constraints of limited channel capacity and limited power. Simulations demonstrate that the current control strategy proposed for MI communication differs significantly from that in the conventional statistical QoS provisioning framework. In addition, compared to other current control strategies, the proposed strategy substantially improves the achievable rate under various delay QoS requirements. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

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Literature Review and Practice Comparison of Technology Foresight

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Procedia Computer Science 2022年 199卷 837-844页

作者： Zhao Minghui Ye Hanrui Peng Yao Zhang Lingling School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China

With continuous breakthrough of key technologies, common technologies, emerging technologies, cross technologies, and subversive technologies, which have brought profound changes to politics, economy, society, culture, and environment. Under above-mentioned background, further exert the guiding role of technology foresight in technology planning formulation, further study the supporting role of technology foresight in emerging technology management, which is important for academic research, enterprise practice and government decision-making. This article can be divided into two parts, the literature review part mainly includes published articles, keyword network, citation network, which describes the historical context, current status, future trends, limitations and improvement directions of related research in detail. The practice comparison part mainly includes targets and experts, methods and processes, technologies and fields, which is also a feasible perspective for results evaluating.

关键词： Technology Foresight Literature Review Practice Comparison

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Bidirectional Logits Tree: Pursuing Granularity Reconcilement in Fine-Grained Classification

arXiv

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arXiv 2024年

作者： Lu, Zhiguang Xu, Qianqian Bao, Shilong Yang, Zhiyong Huang, Qingming Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China School of Computer Science and Technology University of Chinese Academy of Sciences China Key Laboratory of Big Data Mining and Knowledge Management University of Chinese Academy of Sciences China

This paper addresses the challenge of Granularity Competition in fine-grained classification tasks, which arises due to the semantic gap between multi-granularity labels. Existing approaches typically develop independent hierarchy-aware models based on shared features extracted from a common base encoder. However, because coarse-grained levels are inherently easier to learn than finer ones, the base encoder tends to prioritize coarse feature abstractions, which impedes the learning of fine-grained features. To overcome this challenge, we propose a novel framework called the Bidirectional Logits Tree (BiLT) for Granularity Reconcilement. The key idea is to develop classifiers sequentially from the finest to the coarsest granularities, rather than parallelly constructing a set of classifiers based on the same input features. In this setup, the outputs of finer-grained classifiers serve as inputs for coarser-grained ones, facilitating the flow of hierarchical semantic information across different granularities. On top of this, we further introduce an Adaptive Intra-Granularity Difference Learning (AIGDL) approach to uncover subtle semantic differences between classes within the same granularity. Extensive experiments demonstrate the effectiveness of our proposed method. Copyright © 2024, The Authors. All rights reserved.

关键词： Coarse-grained modeling

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MambaLCT: Boosting Tracking via Long-term Context State Space Model 39

MambaLCT: Boosting Tracking via Long-term Context State Spac...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Li, Xiaohai Zhong, Bineng Liang, Qihua Li, Guorong Mo, Zhiyi Song, Shuxiang Key Laboratory of Education Blockchain and Intelligent Technology Ministry of Education Guangxi Normal University Guilin541004 China Guangxi Colleges Universities Key Laboratory of Intelligent Software Wuzhou University Wuzhou543002 China Key Laboratory of Big Data Mining and Knowledge Management University of Chinese Academy of Sciences Beijing100101 China

ISBN: (纸本)157735897X

Effectively constructing context information with long-term dependencies from video sequences is crucial for object tracking. However, the context length constructed by existing work is limited, only considering object information from adjacent frames or video clips, leading to insufficient utilization of contextual information. To address this issue, we propose MambaLCT, which constructs and utilizes target variation cues from the first frame to the current frame for robust tracking. First, a novel unidirectional Context Mamba module is designed to scan frame features along the temporal dimension, gathering target change cues throughout the entire sequence. Specifically, target-related information in frame features is compressed into a hidden state space through selective scanning mechanism. The target information across the entire video is continuously aggregated into target variation cues. Next, we inject the target change cues into the attention mechanism, providing temporal information for modeling the relationship between the template and search frames. The advantage of MambaLCT is its ability to continuously extend the length of the context, capturing complete target change cues, which enhances the stability and robustness of the tracker. Extensive experiments show that long-term context information enhances the model’s ability to perceive targets in complex scenarios. MambaLCT achieves new SOTA performance on six benchmarks while maintaining real-time running speeds. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Literature Review and Practice Comparison of Technology Foresight 8

Literature Review and Practice Comparison of Technology Fore...

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8th International Conference on Information Technology and Quantitative management, ITQM 2020 and 2021

作者： Minghui, Zhao Hanrui, Ye Yao, Peng Lingling, Zhang School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China

关键词： Decision making

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PathReasoner: Modeling Reasoning Path with Equivalent Extension for Logical Question Answering

arXiv

引用

arXiv 2024年

作者： Xu, Fangzhi Lin, Qika Zhao, Tianzhe Han, Jiawei Liu, Jun School of Computer Science and Technology Xi’an Jiaotong University China Ministry of Education Key Laboratory of Intelligent Networks and Network Security China Shaanxi Province Key Laboratory of Big Data Knowledge Engineering China

Logical reasoning task has attracted great interest since it was proposed. Faced with such a task, current competitive models, even large language models (e.g., ChatGPT and PaLM 2), still perform badly. Previous promising LMs struggle in logical consistency modeling and logical structure perception. To this end, we model the logical reasoning task by transforming each logical sample into reasoning paths and propose an architecture PathReasoner. It addresses the task from the views of both data and model. To expand the diversity of the logical samples, we propose an atom extension strategy supported by equivalent logical formulas, to form new reasoning paths. From the model perspective, we design a stack of transformer-style blocks. In particular, we propose a path-attention module to joint model in-atom and cross-atom relations with the high-order diffusion strategy. Experiments show that PathReasoner achieves competitive performances on two logical reasoning benchmarks and great generalization abilities. © 2024, CC BY.

关键词： Atoms

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Landslide hazard susceptibility evaluation based on SBAS-InSAR technology and SSA-BP neural network algorithm:A case study of Baihetan Reservoir Area

引用

Journal of Mountain Science 2024年第3期21卷 952-972页

作者： GUO Junqi XI Wenfei YANG Zhiquan SHI Zhengtao HUANG Guangcai YANG Zhengrong YANG Dongqing Faculty of Geography Yunnan Normal UniversityKunming 650500China Key Laboratory of Early Rapid Identification Prevention and Control of Geological Diseases in Traffic Corridor of High Intensity Earthquake Mountainous Area of Yunnan ProvinceKunming 650093China Faculty of Public Safety and Emergency Management Kunming University of Science and TechnologyKunming 650093China Key Laboratory of Geological Disaster Risk Prevention and Control and Emergency Disaster Reduction of Ministry of Emergency Management of the People’s Republic of China Kunming University of Science and TechnologyKunming 650093China Guizhou Geological Survey Institute Guiyang 550081China College of Big Data and Intelligent Engineering Southwest Forestry UniversityKunming 650224China

Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and *** order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network *** SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and *** Reservoir area is selected as a case study for *** indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard ***,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,***,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation *** area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation ra

关键词： Baihetan SBAS-InSAR SSA-BP Landslide hazard susceptibility evaluation

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A New Adaptive Image Sharpening Scheme 13

A New Adaptive Image Sharpening Scheme

引用

13th International Conference on Information Technology in Medicine and Education, ITME 2023

作者： Chen, Tzong-Jer Lu, Rong-Hui School of Mathematics & Computer Science Wuyi University Fujian Wuyishan354300 China Wuyi University Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry China Wuyi University Information Technology and Laboratory Management Center Fujian Wuyishan354300 China

ISBN: (纸本)9798350319156

The sharpening is a scheme applied to highlight the intensity transitions in an image. This enhancement increases edge acutance and significantly improves the overall sharpness of processed images. Image sharpening is also of enormous importance in medicine for diagnosis. Noise overshoot and over-sharpening effects occur in traditional sharpening algorithms. The adaptive approach skips the noise producing a better sharpening result. Abrupt pixel value changes, if adequately emphasized, can be utilized effectively in the sharpening process. Since a residual image contains noise with edges, the bigger the filter size the greater the content of edges left in the residual image. Two residual images are produced first with different filter sizes and assumed a relationship between two residuals. A simple linear regression is measured using these residuals. This linear equation is an expectation and the deviation is the difference between two residuals. The window may contain edges if the residual value measured by larger size filter to some degree higher than that by smaller size filter. One standard deviation (±σ) is proposed as the threshold, in this work. A sensitive sharpening filter is adaptively then applied to those locations in image. It has been demonstrated that the proposed approach yields better results than the global sharpening filter on the measurements of Pratt's P indices. A sharpening scheme without latent image noise amplification is useful for pattern recognition and machine-learning. In the future this scheme will be used to preprocess image segmentation and medical image. © 2023 IEEE.

关键词： Image segmentation

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Towards sustainable adversarial training with successive perturbation generation

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Frontiers of Information Technology & Electronic Engineering 2024年第4期25卷 527-539页

作者： Wei LIN Lichuan LIAO College of Computer Science and Mathematics Fujian University of TechnologyFuzhou 350118China College of Economics and Management Xi’an University of TechnologyXi’an 710048China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of TechnologyFuzhou 350118China

Adversarial training with online-generated adversarial examples has achieved promising performance in defending adversarial attacks and improving robustness of convolutional neural network ***,most existing adversarial training methods are dedicated to finding strong adversarial examples for forcing the model to learn the adversarial data distribution,which inevitably imposes a large computational overhead and results in a decrease in the generalization performance on clean *** this paper,we show that progressively enhancing the adversarial strength of adversarial examples across training epochs can effectively improve the model robustness,and appropriate model shifting can preserve the generalization performance of models in conjunction with negligible computational *** this end,we propose a successive perturbation generation scheme for adversarial training(SPGAT),which progressively strengthens the adversarial examples by adding the perturbations on adversarial examples transferred from the previous epoch and shifts models across the epochs to improve the efficiency of adversarial *** proposed SPGAT is both efficient and effective;e.g.,the computation time of our method is 900 min as against the 4100 min duration observed in the case of standard adversarial training,and the performance boost is more than 7%and 3%in terms of adversarial accuracy and clean accuracy,*** extensively evaluate the SPGAT on various datasets,including small-scale MNIST,middle-scale CIFAR-10,and large-scale *** experimental results show that our method is more efficient while performing favorably against state-of-the-art methods.

关键词： Adversarial training Adversarial attack Stochastic weight average Machine learning Model generalization

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