Fuzzy branching temporal logic

Intelligent systems require a systematic way to represent and handle temporal information containing uncertainty. In particular, a logical framework is needed that can represent uncertain temporal information and its relationships with logical formulae. Fuzzy linear temporal logic (FLTL), a generalization of propositional linear temporal logic (PLTL) with fuzzy temporal events and fuzzy temporal states defined on a linear time model, was previously proposed for this purpose. However, many systems are best represented by branching time models in which each state can have more than one possible future path. In this paper, fuzzy branching temporal logic (FBTL) is proposed to address this problem. FBTL adopts and generalizes concurrent tree logic (CTL*), which is a classical branching temporal logic. The temporal model of FBTL is capable of representing fuzzy temporal events and fuzzy temporal states, and the order relation among them is represented as a directed graph. The utility of FBTL is demonstrated using a fuzzy job shop scheduling problem as an example.     

A Fuzzy Temporal Object‐Relational Database: Model and Implementation

In real world, some data have a specific temporal validity that must be appropiately managed. To deal with this kind of data, several proposals of temporal databases have been introduced. Moreover, time can also be affected by imprecision, vagueness, and/or uncertainty, since human beings manage time using temporal indications and temporal notions, which may also be imprecise. For this reason, information systems require appropriate support to accomplish this task. In this work, we present a novel possibilistic valid time model for fuzzy databases including the data structures, the integrity constraints, and the DML. Together with this model, we also present its implementation by means of a fuzzy valid time support module on top of a fuzzy object‐relational database system. The integration of these modules allows to perform queries that combines fuzzy valid time constraints together with fuzzy predicates. Besides, the model and implementation proposed support the crisp valid time model as a particular case of the fuzzy valid time support provided.     

基于状态和变化的统一时空数据模型

提出了一个基于状态和变化的统一时空数据模型SCUDM(state and change based unified spatio-temporial datamodel).时空数据库的状态是关于对象、空间和时间的三元组,时空数据库的变化就是状态的变化.按照对象域、空间域和时间域将时空数据库中的变化分别投影分解,显式地表达在对象、空间和时间上的变化.而事件是在某一时刻前后,时空实体的变化关系,在事件表达中蕴涵了空间实体之间的时间拓扑关系.SCUDM不仅支持状态和变化的表达,而且支持时间拓扑和空间拓扑的表达.     

A conceptual schema-based temporal meta database schemas generation technique for 3D objects

In this paper, a temporal meta database for three-dimensional (3D) objects whose properties and relationships are supported by valid time is introduced. Based on our proposed temporal object-oriented conceptual schema model, a conceptual schema of the temporal meta database can be generated from a 3D graphical data source and other particular application requirements. Based on our proposed temporal object relational data model with attribute timestamping, logical schemas of the temporal meta database can be systematically and automatically generated from the conceptual schema. From the temporal meta database, non-temporal/temporal metadata about temporal 3D objects are available for temporal information system users. Convenient access using database languages such as SQL can be performed. Queries over 3D objects using a temporal object relational SQL are demonstrated.     

A logic programming framework for modeling temporal objects

We present a general approach for modeling temporal aspects of objects in a logic programming framework. Change is formulated in the context of a database which stores explicitly a record of all changes that have occurred to objects and thus (implicitly) all states of objects in the database. A snapshot of the database at any given time is an object-oriented database, in the sense that it supports an object-based data model. An object is viewed as a collection of simple atomic formulas, with support for an explicit notion of object identity, classes and inheritance. The event calculus is a treatment of time and change in first-order classical logic augmented with negation as failure. The paper develops a variant of the event calculus for representing changes to objects, including change in internal state of objects, creation and deletion of objects, and mutation of objects over time. The concluding sections present two natural and straightforward extensions, to deal with versioning of objects and schema evolution, and a sketch of implementation strategies for practical application to temporal object-oriented databases     

Learning and parsing video events with goal and intent prediction

In this paper, we present a framework for parsing video events with stochastic Temporal And–Or Graph (T-AOG) and unsupervised learning of the T-AOG from video. This T-AOG represents a stochastic event grammar. The alphabet of the T-AOG consists of a set of grounded spatial relations including the poses of agents and their interactions with objects in the scene. The terminal nodes of the T-AOG are atomic actions which are specified by a number of grounded relations over image frames. An And-node represents a sequence of actions. An Or-node represents a number of alternative ways of such concatenations. The And–Or nodes in the T-AOG can generate a set of valid temporal configurations of atomic actions, which can be equivalently represented as the language of a stochastic context-free grammar (SCFG). For each And-node we model the temporal relations of its children nodes to distinguish events with similar structures but different temporal patterns and interpolate missing portions of events. This makes the T-AOG grammar context-sensitive. We propose an unsupervised learning algorithm to learn the atomic actions, the temporal relations and the And–Or nodes under the information projection principle in a coherent probabilistic framework. We also propose an event parsing algorithm based on the T-AOG which can understand events, infer the goal of agents, and predict their plausible intended actions. In comparison with existing methods, our paper makes the following contributions. (i) We represent events by a T-AOG with hierarchical compositions of events and the temporal relations between the sub-events. (ii) We learn the grammar, including atomic actions and temporal relations, automatically from the video data without manual supervision. (iii) Our algorithm infers the goal of agents and predicts their intents by a top-down process, handles events insertion and multi-agent events, keeps all possible interpretations of the video to preserve the ambiguities, and achieves the globally optimal parsing solution in a Bayesian framework. (iv) The algorithm uses event context to improve the detection of atomic actions, segment and recognize objects in the scene. Extensive experiments, including indoor and out door scenes, single and multiple agents events, are conducted to validate the effectiveness of the proposed approach.     

Constraint analysis: a design process for specifying operations onobjects

A design process for an object-oriented database design environment, known as constraint analysis, is presented. Given the increased level of semantics associated with an object-oriented database schema, constraint analysis makes use of semantics expressed as database constraints to support the flexible specification of propagation actions for operations on objects. Constraints are formally represented using Horn logic. The constraint analysis process then reasons about constraints at design time to help the designer understand the effects of constraints on object manipulation, identifying possible constraint violations as well as design alternatives for handling violations. An advantage of constraint analysis is that both inherent and explicit schema constraints are included in the analysis process. A formal representation is given that supports the analysis of constraints and the automatic identification of design alternatives for responding to constraint violations     

A METHOD FOR TEMPORAL KNOWLEDGE INTEGRATION USING INDETERMINATE MODEL OF TIME

Integration of knowledge is one of the most important tasks for knowledge management in distributed environments. For the same subject in the real world, each different source may generate different versions of data. Of course, with local integrity constraints these data are consistent, but they may be inconsistent with global integrity constraints. This is a popular phenomenon in processing data from distributed sources in the real world. In this work we will investigate processing inconsistency of knowledge and its integration process using the temporal model of indeterminate valid time and probability. This data model is used to describe events that take place in the future with some certainty degrees. With this model, conflict is considered as a situation in which for the same event agents give different time intervals and probabilities about the occurrence of that event. In the integration process we need to determine a proper time interval and probability (based on consensus method) that properly represent that event. With this aim, two kinds of distance functions are defined as well as analyzed. In addition, some postulates and algorithms for knowledge integration are also worked out and analyzed.     

面向RFID数据处理的复杂事件模式匹配方法

RFID数据具有不确定性,复杂事件处理技术将RFID数据看作不同类型的事件,从事件流中检测符合特定匹配模式的复杂事件。概率事件流分为多项概率事件流和单项概率事件流;针对多项概率事件流,提出NFA-MMG模式匹配方法,亦即使用多个有向无环图结合自动机实现模式匹配。针对单项概率事件流,提出NFA-Tree模式匹配方法,亦即使用匹配树结合自动机实现模式匹配;并提出改进的NFA-Tree方法,即基于概率阈值进行过滤,提高结果过滤效率。实验结果验证了上述模式匹配方法的性能优势。     

移动数据库中的事件及描述

在移动计算环境中,移动主机具有移动性,移动主机与无线网络的连接状态具有多样性.这些特性要求服务于移动主机的移动数据库系统作出反应和相应的处理.在建立一个主动数据库ECA(event condition action)规则系统模型的基础上,对各种移动事件进行定义,给出了事件的时态逻辑描述,为主动数据库的事件触发提供了新的事件空间,为移动数据库系统的主动处理提供了有效的支持.     

The time model for event processing in internet of things

The time management model for event processing in internet of things has a special and important requirement. Many events in real world applications are long-lasting events which have different time granularity with order or out-of-order. The temporal relationships among those events are often complex. An important issue of complex event processing is to extract patterns from event streams to support decision making in real-time. However, current time management model does not consider the unified solution about time granularity, time interval, time disorder, and the difference between workday calendar systems in different organizations. In this work, we analyze the preliminaries of temporal semantics of events. A tree-plan model of out-of-order durable events is proposed. A hybrid solution is correspondingly introduced. A case study is illustrated to explain the time constraints and the time optimization. Extensive experimental studies demonstrate the efficiency of our approach.     

PROBE spatial data modeling and query processing in an imagedatabase application

The PROBE research project has produced results in the areas of data modeling, spatial/temporal query processing, recursive query processing, and database system architecture for nontraditional application areas, many of which involve spatial data and data with complex structure. An overview of PROBE is provided, focusing on the facilities for dealing with spatial and temporal data. It is shown how the PROBE database system and simple application-specific object classes combine to efficiently support PROBE's spatial data model. It is also shown how an image-database application can be supported using PROBE's data model and spatial query processor. The current status of the PROBE project and future plans are discussed     

Development of a Temporal Extension to Query Travel Behavior Time Paths Using an Object-Oriented GIS

An essential requirement to better understand activity-based travel behavior (ABTB) at the disaggregate level is the development of a spatio-temporal model able to support queries related to activities of individuals or groups of individuals. This paper describes the development and implementation of a temporal extension to a geographic information system (GIS) object-oriented model for the modeling of the time path and the retrieval of its event chaining. In this approach, time path is formulated as a totally time ordered set composed by activity events and trip events, themselves organized into time ordered sets. As sets, the time path and its components can be searched using their respective indexes. A series of methods were built that implement temporal predicates as an interface to temporally query the database. A set of positional operator methods were also designed that transform temporal topological queries into retrieval functions based on set ordering indices. Taken together, the temporal predicates and the positional operator methods define a temporal query extension that meets the retrieval needs of an ABTB database.     

An algebraic framework for temporal attribute characteristics

Most real-world database applications manage temporal data, i.e., data with associated time references that capture a temporal aspect of the data, typically either when the data is valid or when the data is known. Such applications abound in, e.g., the financial, medical, and scientific domains. In contrast to this, current database management systems offer preciously little built-in query language support for temporal data management. This situation persists although an active temporal database research community has demonstrated that application development can be simplified substantially by built-in temporal support. This paper's contribution is motivated by the observation that existing temporal data models and query languages generally make the same rigid assumption about the semantics of the association of data and time, namely that if a subset of the time domain is associated with some data then this implies the association of any further subset with the data. This paper offers a comprehensive, general framework where alternative semantics may co-exist. It supports so-called malleable and atomic temporal associations, in addition to the conventional ones mentioned above, which are termed constant. To demonstrate the utility of the framework, the paper defines a characteristics-enabled temporal algebra, termed CETA, which defines the traditional relational operators in the new framework. This contribution demonstrates that it is possible to provide built-in temporal support while making less rigid assumptions about the data and without jeopardizing the degree of the support. This moves temporal support closer to practical applications.     

Effective timestamping in databases

Many existing database applications place various timestamps on their data, rendering temporal values such as dates and times prevalent in database tables. During the past two decades, several dozen temporal data models have appeared, all with timestamps being integral components. The models have used timestamps for encoding two specific temporal aspects of database facts, namely transaction time, when the facts are current in the database, and valid time, when the facts are true in the modeled reality. However, with few exceptions, the assignment of timestamp values has been considered only in the context of individual modification statements. This paper takes the next logical step: It considers the use of timestamping for capturing transaction and valid time in the context of transactions. The paper initially identifies and analyzes several problems with straightforward timestamping, then proceeds to propose a variety of techniques aimed at solving these problems. Timestamping the results of a transaction with the commit time of the transaction is a promising approach. The paper studies how this timestamping may be done using a spectrum of techniques. While many database facts are valid until now, the current time, this value is absent from the existing temporal types. Techniques that address this problem using different substitute values are presented. Using a stratum architecture, the performance of the different proposed techniques are studied. Although querying and modifying time-varying data is accompanied by a number of subtle problems, we present a comprehensive approach that provides application programmers with simple, consistent, and efficient support for modifying bitemporal databases in the context of user transactions. Received: March 11, 1998 / Accepted July 27, 1999     

有效的BCDM时态信息简化方法

时态信息是管理决策中的重要支持信息,需求的不同造就了时态信息不同的表示方法.随着数据库与信息技术的深入发展,越来越需要简单高效的时态数据模型以方便时态信息的表示与处理.介绍了BCDM模型及其时态表示思想,讨论了模型中事务时间和有效时间表示在查询优化时存在的问题,提出了一种基于BCDM的时态信息简化方法,不但能够有效的保存数据库现有的时态信息,而且能够大大简化有效时间的表示,为时态数据的查询优化奠定了良好基础.     

CoreFlow: Extracting and Visualizing Branching Patterns from Event Sequences

Event sequence datasets with high event cardinality and long sequences are difficult to visualize and analyze. In particular, it is hard to generate a high level visual summary of paths and volume of flow. Existing approaches of mining and visualizing frequent sequential patterns look promising, but have limitations in terms of scalability, interpretability and utility. We propose CoreFlow, a technique that automatically extracts and visualizes branching patterns in event sequences. CoreFlow constructs a tree by recursively applying a three‐step procedure: rank events, divide sequences into groups, and trim sequences by the chosen event. The resulting tree contains key events as nodes, and links represent aggregated flows between key events. Based on CoreFlow, we have developed an interactive system for event sequence analysis. Our approach can compute branching patterns for millions of events in a few seconds, with improved interpretability of extracted patterns compared to previous work. We also present case studies of using the system in three different domains and discuss success and failure cases of applying CoreFlow to real‐world analytic problems. These case studies call forth future research on metrics and models to evaluate the quality of visual summaries of event sequences.     

Issues in query model design in object-oriented database systems

The provision of a powerful query system, including a declarative query language and the systems support for efficiently processing queries is essential for the success of object-oriented database technology. Designing a query system involves making a large number of decisions, further complicated by the lack of a universally accepted object-oriented object data model. In this paper, object data model and query model design decisions are enumerated, alternatives are identified, and the tradeoffs are specified.     

时态数据库在研究生信息管理中的应用

采用时态数据库对不同时期的研究生信息及研究生规则进行管理。研究生信息中含有很多与时间有关的信息,比如入学时间,研究生个人信息与研究生成绩的有效时间等。规则具有时态性,不同的时期有不同的规则,当前只适用当前有效的规则。传统数据库很难体现数据的时态性,在时间处理方面也遇到很大挑战。结果表明时态数据库在时间运算和处理方面有独到的优势,显示出了极大的优越性。