Information Systems最新文献_第3页

GlintLM: Graph-Layered Integration with Nodal Topology with Language Models — A Bipartite Approach to Question Answering 基于语言模型的节点拓扑的图层集成——一种二分法的问题回答方法

IF 3.4 2区计算机科学

Information Systems Pub Date : 2025-08-20 DOI: 10.1016/j.is.2025.102610

ZhuoFan Chen , Yao Hui Hoon , Renne Ye Kai Ong , Justin Juin Hng Wong

{"title":"GlintLM: Graph-Layered Integration with Nodal Topology with Language Models — A Bipartite Approach to Question Answering","authors":"ZhuoFan Chen , Yao Hui Hoon , Renne Ye Kai Ong , Justin Juin Hng Wong","doi":"10.1016/j.is.2025.102610","DOIUrl":"10.1016/j.is.2025.102610","url":null,"abstract":"<div><div>In modern Question Answering (QA) systems, Language Models (LMs) are often combined with Knowledge Graphs (KGs) to better handle challenges like word ambiguity and complex sentence structures. This combination helps LMs gain a deeper understanding by grounding them in structured knowledge. However, existing approaches often fall short in two areas: (1) they do not fully use the features of Knowledge Graphs and Graph Neural Networks (GNNs) during reasoning, and (2) they miss opportunities to better rank and filter information using the outputs of LMs and GNNs. To address this, we propose GlintLM, a system with two key innovations. First, the Enhanced Topological Node Representation (ETNR) module, which uses graph structure and a custom node feature method to improve reasoning. Second, the Multiplex Contextual Scorer (MCS) module, which combines pre-trained LM outputs with GNN attention to better score and filter relevant nodes. Together, these components create a more effective and adaptable system for QA. GlintLM demonstrates improved performance on common-sense (CommonsenseQA, OpenBookQA) and biomedical (MedQA-USMLE) QA benchmarks, showing improved performance across commonsense and medical domains.<span><span><sup>2</sup></span></span></div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"135 ","pages":"Article 102610"},"PeriodicalIF":3.4,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144890473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CrossER: A robust and adaptable generalized entity resolution framework for diverse and heterogeneous datasets CrossER：一个鲁棒且适应性强的通用实体解析框架，适用于各种异构数据集

IF 3.4 2区计算机科学

Information Systems Pub Date : 2025-08-14 DOI: 10.1016/j.is.2025.102609

Yunong Tian , Ning Wang , Anshun Zhou

{"title":"CrossER: A robust and adaptable generalized entity resolution framework for diverse and heterogeneous datasets","authors":"Yunong Tian , Ning Wang , Anshun Zhou","doi":"10.1016/j.is.2025.102609","DOIUrl":"10.1016/j.is.2025.102609","url":null,"abstract":"<div><div>Entity Resolution (ER) is a critical task in data cleaning and integration, traditionally focusing on structured relational tables with aligned schemas. However, real-world applications often involve diverse data formats, leading to the emergence of Generalized Entity Resolution, which addresses structured, semi-structured, and unstructured data. While prompt-based methods have shown promise in improving entity resolution, they suffer from significant limitations such as sensitivity to prompt design and instability across heterogeneous data formats. To address these challenges, we propose CrossER, a novel framework that integrates cross-attention mechanisms, contrastive learning, and data augmentation. CrossER employs a cross-attention module to dynamically align attributes across heterogeneous data sources, enabling accurate entity resolution. To enhance robustness, contrastive learning constructs discriminative feature representations, and data augmentation introduces variability to improve adaptability to noisy and complex datasets. Experimental results on multiple real-world datasets demonstrate that CrossER significantly outperforms state-of-the-art Generalized Entity Resolution methods in F1 scores while maintaining computational efficiency. Furthermore, CrossER exhibits minimal dependency on specific pre-trained language models and delivers superior recall rates compared to baseline methods, especially in challenging heterogeneous datasets.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"135 ","pages":"Article 102609"},"PeriodicalIF":3.4,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144858374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Density based learned spatial index for clustered data 基于密度的聚类数据学习空间索引

IF 3.4 2区计算机科学

Information Systems Pub Date : 2025-08-11 DOI: 10.1016/j.is.2025.102606

Xiaofei Zhao, Kam-Yiu Lam

{"title":"Density based learned spatial index for clustered data","authors":"Xiaofei Zhao, Kam-Yiu Lam","doi":"10.1016/j.is.2025.102606","DOIUrl":"10.1016/j.is.2025.102606","url":null,"abstract":"<div><div>Retrieving spatial points, such as GPS records or Point of Interests, that satisfy specific location-based query criteria is a core operation in location-based services. Recent studies have shown that learned indexes can outperform traditional indexing methods in both query performance and space efficiency by leveraging data distribution to construct compact predictive models. On the other hand, traditional indexes typically make minimal assumptions about the underlying data distribution. In real-world spatial databases, data is often non-uniformly distributed and tends to cluster in specific regions or along road networks. Adaptivity to such data patterns may bring performance benefits.</div><div>In this paper, we explore the construction of efficient learned indexes that exploit the clustering characteristics of spatial datasets. Specifically, we propose a Density-based Grid Learning Spatial Index (DGLSI), which partitions the spatial domain based on point density and utilizes learned models, including multiple recursive model indexes to predict the grid cell IDs of query points. We evaluate DGLSI’s performance on real-world GPS datasets and demonstrate that the proposed methods outperform analogous grid-based indexes across various query workloads, including nearest point queries and range queries while maintaining high space efficiency.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"135 ","pages":"Article 102606"},"PeriodicalIF":3.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-source data outlier detection based on secure multi-party computation 基于安全多方计算的多源数据离群点检测

IF 3.4 2区计算机科学

Information Systems Pub Date : 2025-08-05 DOI: 10.1016/j.is.2025.102597

Lin Yao , Zhaolong Zheng , Tian Wei , Guowei Wu

{"title":"Multi-source data outlier detection based on secure multi-party computation","authors":"Lin Yao , Zhaolong Zheng , Tian Wei , Guowei Wu","doi":"10.1016/j.is.2025.102597","DOIUrl":"10.1016/j.is.2025.102597","url":null,"abstract":"<div><div>Outlier detection has been applied to many fields such as financial fraud, fault detection, and health diagnosis as an important technology to discover abnormal data. Data sharing is required to perform outlier detection on multi-source data. However, data sharing between multi-source generally discloses privacy embedded within the data such as sensitive patient information. With the increasing emphasis on personal privacy, it is necessary to study how to achieve outlier detection for multi-source data while preserving privacy. Secure Multi-Party Computation (SMPC) is a privacy-preserving technology to achieve secure calculation between multi-source in the absence of a trusted third party. But due to frequent data interaction, high complexity and low practicability comes with complex calculations. In this paper, we propose a secure multi-source data outlier detection scheme based on SMPC. Our scheme uses homomorphic encryption and perturbation to preserve the critical process of calculating the global distance matrix, which greatly reduces the complexity of the secure calculation process. Besides, we design an outlier determination strategy to reduce the steps of searching reverse neighbors and calculating the final local outlier factor. By comparison, our scheme outperforms the existing schemes in terms of accuracy ratio, running time and efficiency.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"135 ","pages":"Article 102597"},"PeriodicalIF":3.4,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144771835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On the evaluation and optimization of LabeledPAM LabeledPAM的评价与优化

IF 3.4 2区计算机科学

Information Systems Pub Date : 2025-07-22 DOI: 10.1016/j.is.2025.102580

Miriama Jánošová , Andreas Lang , Petra Budikova , Erich Schubert , Vlastislav Dohnal

{"title":"On the evaluation and optimization of LabeledPAM","authors":"Miriama Jánošová , Andreas Lang , Petra Budikova , Erich Schubert , Vlastislav Dohnal","doi":"10.1016/j.is.2025.102580","DOIUrl":"10.1016/j.is.2025.102580","url":null,"abstract":"<div><div>The analysis of complex and weakly labeled data is increasingly popular. Traditional unsupervised clustering aims to uncover interrelated sets of objects based on feature-based similarity. This approach often reaches its limits when dealing with complex multimedia data due to the curse of dimensionality, presenting unique challenges. Semi-supervised clustering, which leverages small amounts of labeled data, has the potential to cope with this problem.</div><div>In this work, we delve into LabeledPAM, a semi-supervised clustering method, which extends FasterPAM, a state-of-the-art <span><math><mi>k</mi></math></span>-medoids clustering algorithm. Our algorithm is designed for both semi-supervised classification, where labels are assigned to clusters with minimal labeled data, and semi-supervised clustering, where new clusters with unknown labels are identified. We propose an optimization to the original LabeledPAM algorithm that reduces its computational complexity. Additionally, we provide an implementation in Rust, which integrates seamlessly with Python libraries.</div><div>To assess LabeledPAM’s performance, we empirically evaluate its properties by comparing it against a range of semi-supervised clustering algorithms, including density-based ones. We conduct experiments on a collection of real-world datasets. Our results demonstrate that LabeledPAM achieves competitive clustering quality while maintaining efficiency across various scenarios, showing its versatility for real-world applications.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"135 ","pages":"Article 102580"},"PeriodicalIF":3.4,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144767116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comprehensive characterization of concept drifts in process mining 工艺采矿中概念漂移的综合表征

IF 3.4 2区计算机科学

Information Systems Pub Date : 2025-07-19 DOI: 10.1016/j.is.2025.102584

Alexander Kraus , Han van der Aa

{"title":"Comprehensive characterization of concept drifts in process mining","authors":"Alexander Kraus , Han van der Aa","doi":"10.1016/j.is.2025.102584","DOIUrl":"10.1016/j.is.2025.102584","url":null,"abstract":"<div><div>Business processes are subject to changes due to the dynamic environments in which they are executed. These process changes can lead to concept drifts, which are situations when the characteristics of a business process have undergone significant changes, resulting in event logs that contain data on different versions of a process. The accuracy and usefulness of process mining results derived from such event logs may be compromised because they rely on historical data that no longer reflects the current process behavior, or because the results do not distinguish between different process versions. Therefore, concept drift detection in process mining aims to identify drifts recorded in an event log by detecting when they occurred, localizing process modifications, and characterizing how they manifest over time. This paper focuses on the latter task, i.e., drift characterization, which seeks to understand whether changes unfolded suddenly or gradually and if they form complex patterns like incremental or recurring drifts. However, current solutions for automatically detecting concept drifts from event logs lack comprehensive characterization capabilities. Instead, they mainly focus on drift detection and characterization of isolated process changes. This leads to an incomplete understanding of more complex concept drifts, like incremental and recurring drifts, when several process changes are inter-connected. This paper overcomes such limitations by introducing an improved taxonomy for characterizing concept drifts and a three-step framework that provides an automatic characterization of concept drifts from event logs. We evaluated our framework through elaborate evaluation experiments conducted using a large collection of synthetic event logs. The results highlight the effectiveness and accuracy of our proposed framework and show that it outperforms state-of-the-art techniques.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"135 ","pages":"Article 102584"},"PeriodicalIF":3.4,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144738344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Low-code solutions for business process dataflows: From modeling to execution 业务流程数据流的低代码解决方案：从建模到执行

IF 3 2区计算机科学

Information Systems Pub Date : 2025-07-18 DOI: 10.1016/j.is.2025.102577

Ali Nour Eldin , Jonathan Baudot , Benjamin Dalmas , Walid Gaaloul

{"title":"Low-code solutions for business process dataflows: From modeling to execution","authors":"Ali Nour Eldin , Jonathan Baudot , Benjamin Dalmas , Walid Gaaloul","doi":"10.1016/j.is.2025.102577","DOIUrl":"10.1016/j.is.2025.102577","url":null,"abstract":"<div><div>Business Process Modeling and Notation (BPMN) is a widely adopted standard for modeling business workflows. However, the increasing complexity and integration of data within business processes demand a modeling language capable of clearly expressing both process and data perspectives. While BPMN effectively represents process control flows, it inadequately addresses critical data-related aspects such as data flow, data dependencies, and data transformations. Moreover, communication gaps and differing interpretations of process requirements frequently arise between developers and business analysts, leading to errors and delays in process implementation and execution.</div><div>To address these limitations, this paper introduces an extension of BPMN, termed the Business Process and Data Modeling Language (BPDML). BPDML is a low-code modeling language specifically designed to capture, model, and execute data-driven business processes. By adopting a low-code approach, BPDML bridges the gap between business analysts and developers, facilitating faster development and delivery of business applications with reduced effort and minimal manual coding. In addition, a specialized modeling tool has been developed to support the creation, validation, and execution of models using BPDML. Both quantitative and qualitative evaluations demonstrate that BPDML significantly enhances the clarity, efficiency, and overall effectiveness of business process modeling and implementation compared to traditional BPMN.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"135 ","pages":"Article 102577"},"PeriodicalIF":3.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Temporal relational algebras supporting preferences in temporal relational databases: Definition, properties and evaluation 支持时态关系数据库中首选项的时态关系代数：定义、属性和评估

IF 3 2区计算机科学

Information Systems Pub Date : 2025-07-17 DOI: 10.1016/j.is.2025.102583

Luca Anselma , Antonella Coviello , Davide Cerotti , Erica Raina , Paolo Terenziani

{"title":"Temporal relational algebras supporting preferences in temporal relational databases: Definition, properties and evaluation","authors":"Luca Anselma , Antonella Coviello , Davide Cerotti , Erica Raina , Paolo Terenziani","doi":"10.1016/j.is.2025.102583","DOIUrl":"10.1016/j.is.2025.102583","url":null,"abstract":"<div><div>Despite numerous approaches address the treatment of time within relational contexts, temporal preferences remain unexplored. Many tasks and applications, such as planning, scheduling, workflows, and guidelines, involve scenarios where the exact timing of events is not known — referred to as <em>indeterminate time</em>. In such cases, preferences can be assigned to different possible temporal outcomes. In a recent study, we established the theoretical foundation for handling preferential indeterminate time in temporal relational databases. This includes proposing a temporal relational representation and a corresponding temporal relational algebra, along with an analysis of their theoretical properties, such as correctness and reducibility.</div><div>The contributions of this paper are twofold. First, we extend the above theoretical framework to deal with a more expressive representation of temporal preferences. Second, we assess both theoretical frameworks in terms of performance evaluation along different dimensions, and study the overhead added to cope with preferences with respect to relational approaches without time, with exact time, and with indeterminate time but no preferences.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"135 ","pages":"Article 102583"},"PeriodicalIF":3.0,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A comprehensive approach to improving CLIP-based image retrieval while maintaining joint-embedding alignment 一种改进基于clip的图像检索同时保持关节嵌入对齐的综合方法

IF 3 2区计算机科学

Information Systems Pub Date : 2025-07-08 DOI: 10.1016/j.is.2025.102581

Konstantin Schall , Kai Uwe Barthel , Nico Hezel , Andre Moelle

{"title":"A comprehensive approach to improving CLIP-based image retrieval while maintaining joint-embedding alignment","authors":"Konstantin Schall , Kai Uwe Barthel , Nico Hezel , Andre Moelle","doi":"10.1016/j.is.2025.102581","DOIUrl":"10.1016/j.is.2025.102581","url":null,"abstract":"<div><div>Contrastive Language–Image Pre-training (CLIP) jointly optimizes an image encoder and a text encoder, yet its semantic supervision can blur the distinction between visually different images that share similar captions, hurting instance-level image retrieval. We study two strategies, two-stage fine-tuning (2SFT) and multi-caption-image pairing (MCIP) that strengthen CLIP models for content-based image retrieval while preserving their cross-modal strengths. 2SFT first adapts the image encoder for retrieval and then realigns the text encoder. MCIP injects multiple pseudo-captions per image so that class labels sharpen retrieval and the extra captions keep text alignment. This extended version augments the original SISAP24 study with experiments on additional models, a systematic investigation of key hyperparameters of the presented approach, insights into the effects of the methods on the model, and more a detailed report on training setting and costs. Across four CLIP model families, the proposed methods boost image-to-image retrieval accuracy without sacrificing text-to-image performance, simplifying large-scale multimodal search systems by allowing them to store one embedding per image while being effective in image-to-image and text-to-image search.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"134 ","pages":"Article 102581"},"PeriodicalIF":3.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Refining the process picture: Unstructured data in object-centric process mining 细化流程图：以对象为中心的流程挖掘中的非结构化数据

IF 3 2区计算机科学

Information Systems Pub Date : 2025-07-08 DOI: 10.1016/j.is.2025.102582

Andreas Egger , Tobias Fehrer , Wolfgang Kratsch , Niklas Wördehoff , Fabian König , Maximilian Röglinger

{"title":"Refining the process picture: Unstructured data in object-centric process mining","authors":"Andreas Egger , Tobias Fehrer , Wolfgang Kratsch , Niklas Wördehoff , Fabian König , Maximilian Röglinger","doi":"10.1016/j.is.2025.102582","DOIUrl":"10.1016/j.is.2025.102582","url":null,"abstract":"<div><div>Process mining aims to discover, monitor, and improve processes. To this end, process mining techniques use event data, typically extracted from information systems and organized along process instances. The inherent complexity of real-world processes has driven the recent introduction of object-centric process mining, allowing for a more comprehensive view of processes. Another avenue of research contributing to more complete process analyses is integrating unstructured data, which can enhance traditional event logs by extracting hitherto unidentified process information. Although combining the object-centric perspective with event log enrichment from unstructured data sources holds promising potential, such investigation remains in its infancy. Against this background, this study presents the OCRAUD, a reference architecture that provides guidance on using unstructured data sources and traditional event logs for object-centric process mining. A design science research process was employed to design and evaluate the OCRAUD. This involved conducting a total of 20 expert interviews over two rounds, comparing the OCRAUD to competing artifacts, instantiating the artifact for the use of video and sensor data, developing a software prototype, and applying the prototype to real-world data. This work contributes to process mining by guiding the combination of unstructured data with traditional event logs, incorporating an object-centric representation of event data. The instantiation targets video and sensor data, thereby demonstrating the use of the artifact. This enables researchers and practitioners to instantiate the artifact for other data types or specific use cases. The published code of the software prototype allows for further development of the implemented algorithms.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"134 ","pages":"Article 102582"},"PeriodicalIF":3.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0