Predicate Detection Research Articles

The <img src=image/13426661_01.gif>-prime Radicals in Posets

A relation is a mathematical tool for describing set relationships. Relationships are common in databases and scheduling applications. Science and engineering are designed to help humans make better decisions. To make these choices, we must first understand human expectations, the outcomes of various options, and the degree of confidence. With all of these data, partial orders will be generated. In several fields of engineering and computer science, partial order and lattice theory are now widely used. To mention a few, they are used in cloud computing (vector clocks, global predicate detection), concurrency theory (pomsets, occurrence nets), programming language semantics (fixed-point semantics), and data mining (concept analysis). Other theoretical disciplines benefit from them as well, such as combinatorics, number theory, and group theory. Partially ordered sets emerge naturally when dealing with multidimensional systems of qualitative ordinal variables in social science, especially to solve ranking, prioritising, and assessment concerns. As an alternative to standard techniques, partial order theory and partially ordered sets can be used to generate composite indicators for evaluating well-being, quality of life, and multidimensional poverty. They can be applied in multi-criteria analysis or for decision-making purposes in the study of individual and social desires, including in social choice theory. They're also valuable in social network analysis, where they may be utilized to apply mathematics to explore network topologies and dynamics. The Hasse diagram method, for example, produces a partial order with multiple incomparabilities (lack of order) between pairs of items. This is a common problem in ranking studies, and it can often be avoided by combining object attributes that lead to a complete order. However, such a mix introduces subjectivity and prejudice into the rating process. This work discusses the notion of a <img src=image/13426661_01.gif>-prime radical of a partially ordered set with respect to ideal. In posets, we investigated the concept of <img src=image/13426661_01.gif>-primary ideals. It is investigated how to characterise <img src=image/13426661_01.gif>-primary ideals in relation to <img src=image/13426661_01.gif>-prime radicals. In addition, an ideal's <img src=image/13426661_01.gif>-primary decomposition is constructed.

Video Visual Relation Detection via 3D Convolutional Neural Network

Video visual relation detection, which aims to detect the visual relations between objects in the form of relation triplet &#x003C;subject, predicate, object&#x003E; (<i>e.g.</i>, &#x201C;person-ride-bike&#x201D;, &#x201C;dog-toward-car&#x201D;, <i>etc.</i>), is a significant and fundamental task in computer vision. However, most of the existing works about visual relation instances are focused on static images. Modeling the non-static relationships in videos has drawn little attention due to lacking large-scale video dataset support. In our work, we propose a video dataset named Video Predicate Detection and Reasoning (VidPDR) for dynamic video visual relation detection, which consists of 1,000 videos with dense manually dynamic labeled annotations on 21 object classes and 37 predicates classes. Moreover, we propose a novel spatio-temporal feature extraction framework with 3D Convolutional Neural Networks (ST3DCNN), which includes three modules <b>1)</b> object trajectory, <b>2)</b> short-term relation prediction, and <b>3)</b> greedy relational association. We conducted appropriate experiments on public datasets and our own dataset (VidPDR). Results demonstrate that our proposed method has a great improvement in comparison to the state-of-the-art baselines.

Multi-task Compositional Network for Visual Relationship Detection

Previous methods treat visual relationship detection as a combination of object detection and predicate detection. However, natural images likely contain hundreds of objects and thousands of object pairs. Relying only on object detection and predicate detection is insufficient for effective visual relationship detection because the significant relationships are easily overwhelmed by the dominant less-significant relationships. In this paper, we propose a novel subtask for visual relationship detection, the significance detection, as the complement of object detection and predicate detection. Significance detection refers to the task of identifying object pairs with significant relationships. Meanwhile, we propose a novel multi-task compositional network (MCN) that simultaneously performs object detection, predicate detection, and significance detection. MCN consists of three modules, an object detector, a relationship generator, and a relationship predictor. The object detector detects objects. The relationship generator provides useful relationships, and the relationship predictor produces significance scores and predicts predicates. Furthermore, MCN proposes a multimodal feature fusion strategy based on visual, spatial, and label features and a novel correlated loss function to deeply combine object detection, predicate detection, and significance detection. MCN is validated on two datasets: visual relationship detection dataset and visual genome dataset. The experimental results compared with state-of-the-art methods verify the competitiveness of MCN and the usefulness of significance detection in visual relationship detection.

Fast Detection of Degenerate Predicates in Free Space Construction

An implementation of a computational geometry algorithm is robust if the combinatorial output is correct for every input. Robustness is achieved by ensuring that the predicates in the algorithm are evaluated correctly. A predicate is the sign of an algebraic expression whose variables are input parameters. The hardest case is detecting degenerate predicates where the value of the expression equals zero. We encounter this case in constructing the free space of a polyhedron that rotates around a fixed axis and translates freely relative to a stationary polyhedron. Each predicate involved in the construction is expressible as the sign of a univariate polynomial [Formula: see text] evaluated at a zero [Formula: see text] of a univariate polynomial [Formula: see text], where the coefficients of [Formula: see text] and [Formula: see text] are polynomials in the coordinates of the polyhedron vertices. A predicate is degenerate when [Formula: see text] is a zero of a common factor of [Formula: see text] and [Formula: see text]. We present an efficient degeneracy detection algorithm based on a one-time factoring of all the univariate polynomials over the ring of multivariate polynomials in the vertex coordinates. Our algorithm is 3500 times faster than the standard algorithm based on greatest common divisor computation. It reduces the share of degeneracy detection in our free space computations from 90% to 0.5% of the running time.

WORK DONE ON MIDDLEWARE INFRASTRUCTURE FOR PREDICATE DETECTION

Context-awareness is an essential feature of pervasive applications, and runtime detection of contextual properties is one of the primary approaches to enabling context awareness. However, existing context-aware middleware does not provide sufficient support for detection of contextual properties in asynchronous environments. The contextual activities usually involve multiple context collecting devices, which are fully-decentralized and interact in an asynchronous manner. However, existing context consistency checking schemes do not work in asynchronous environments, since they implicitly assume the availability of a global clock or relay on synchronized interactions. To this end, we present the Middleware Infrastructure for Predicate detection in Asynchronous environments (MIPA), which supports context awareness based on logical time. Design and Structure of MIPA are explained in detail.

Efficient detection of motion-trend predicates in wireless sensor networks

This work addresses the problem of efficient distributed detection of predicates capturing the motion trends of mobile objects evaluated with respect to a (boundary of a) polygonal region, in the settings in which the (location, time) data is obtained via tracking in Wireless Sensor Networks (WSN). Specifically, we discuss in-network distributed algorithms for detecting two motion-trend predicates: Continuously Moving Towards and Persistently Moving Towards: first for a single object, and then the corresponding variants for multiple objects. We also present methodologies which consider the energy vs. latency trade-offs when multiple tracked objects are being considered for validating the monitored predicates. Our experiments demonstrate that our proposed technique yield substantial energy savings when compared to the naïve centralized and cluster-based approaches in which the raw (location, time) data is transmitted to a dedicated sink where the predicates are being evaluated.

Enabling Context-Awareness by Predicate Detection in Asynchronous Environments

Pervasive applications are involving more and more autonomous computing and communicating devices, augmented with the abilities of sensing and controlling the logical/physical environment. To enable context-awareness for such applications, we are challenged by the intrinsic asynchrony of the computing environment. Predicate detection is a well studied technique dedicated to detecting global predicates over asynchronous computations and can be employed to achieve context-awareness of the asynchronous environment. However, there is no methodological framework which guides us to systematically apply the abstract predicate detection theory to the development of concrete context-aware applications. To this end, we present the Predicate Detection-based Context-Awareness (PD-CA) framework. PD-CA maps the concepts of context-awareness to concepts of predicate detection. PD-CA also presents a design process of providing middleware support for context-aware applications. Under the guidance of the PD-CA framework, we design and implement the Middleware Infrastructure for Predicate detection in Asynchronous environments (MIPA). We also propose the programming toolkit to facilitate the development of context-aware applications based on MIPA, and demonstrate the use of the toolkit by a case study of a chemical plant safety management application. Experimental evaluations show the performance of MIPA in enabling context-awareness despite of the asynchrony.

Predicate Detection in Asynchronous Distributed Systems: A Probabilistic Approach

In an asynchronous distributed system, a number of processes communicate with each other via message passing that has a finite but arbitrary long delay. There is no global clock in that system. Predicates, denoting the states of processes and their relations, are often used to specify the information of interest in such a system. Due to the lack of a global clock, the temporal relations between the states at different processes cannot be uniquely determined, but have multiple possible circumstances. Existing works of predicate detection are based on the definitely modality or the possibly modality, denoting that a predicate holds in all of the possible circumstances or in one of them, respectively. No information is provided about the probability that a predicate will hold, which hinders the taking of countermeasures for different situations. Moreover, the detection is based on single occurrence of a predicate, so the results are heavily affected by environmental noise and detection errors. In this paper, we propose a new approach to predicate detection to address these two issues. We generalize the definitely and possibly modalities to an occurrence probability to provide more detailed information, and further investigate how to detect multiple occurrences of a predicate. We propose a unified algorithm framework for detecting various types of predicates and demonstrate the use of it for three typical types of predicates, including simple predicates, simple sequences, and interval-constrained sequences. Theoretical proofs and simulation results show that our approach is effective and outperforms existing approaches.

Efficient abstraction algorithms for predicate detection

Analyzing a distributed computation is a hard problem in general due to the combinatorial explosion in the size of the state-space with the number of processes in the system. By abstracting the computation, unnecessary state explorations can be avoided. Computation slicing is an approach for abstracting distributed computations with respect to a given predicate. To detect a predicate in a timely manner during run-time verification, it is important to be able to compute the slice in an incremental manner as and when a new event is generated in the system. In this work, we present several online abstraction algorithms for computing the slice of a distributed computation with respect to regular predicates and its temporal extensions. The family of regular predicates is fairly rich and covers many commonly used predicates for run-time verification. We first present several online algorithms for computing the slice with respect to certain temporal logical regular predicates all of which are centralized. We then present a distributed algorithm for computing the slice with respect to a regular state based predicate; it distributes the work and storage requirements across the system, thus reducing the space and computation complexity per process. We also extend the slicing technique to non-regular predicates by presenting algorithms for computing the slice for two temporal logic operators when the predicate used in the operator is not regular.

MIDDLEWARE INFRASTRUCTURE FOR PREDICATE DETECTION IN ASYNCHRONOUS ENVIRONMENT

Context-awareness is an essential feature of pervasive applications, and runtime detection of contextual properties is one of the primary approaches to enabling context awareness. However, existing context-aware middleware does not provide sufficient support for detection of contextual properties in asynchronous environments. The contextual activities usually involve multiple context collecting devices, which are fully-decentralized and interact in an asynchronous manner. However, existing context consistency checking schemes do not work in asynchronous environments, since they implicitly assume the availability of a global clock or relay on synchronized interactions. To this end, we present the Middleware Infrastructure for Predicate detection in Asynchronous environments (MIPA), which supports context awareness based on logical time. Design and Structure of MIPA are explained in detail.

A parallel algorithm for global states enumeration in concurrent systems

Verifying the correctness of the executions of a concurrent program is difficult because of its nondeterministic behavior. One of the verification methods is predicate detection, which predicts whether the user specified condition (predicate) could become true in any global states of the program. The method is predictive because it generates inferred execution paths from the observed execution path and then checks the predicate on the global states of inferred paths. One important part of predicate detection is global states enumeration, which generates the global states on inferred paths. Cooper and Marzullo gave the first enumeration algorithm based on a breadth first strategy (BFS). Later, many algorithms have been proposed to improve space and time complexity. None of them, however, takes parallelism into consideration. In this paper, we present the first parallel and online algorithm, named ParaMount, for global state enumeration. Our experimental results show that ParaMount speeds up the existing sequential algorithms by a factor of 6 with 8 threads. We have implemented an online predicate detector using ParaMount. For predicate detection, our detector based on ParaMount is 10 to 50 times faster than RV runtime (a verification tool that uses Cooper and Marzullo’s BFS enumeration algorithm).

Hierarchical Detection of Strong Unstable Conjunctive Predicates in Large-Scale Systems

In large-scale systems where an on-going monitoring program is needed, the traditional predicate detection algorithms become undesirable due to their high overhead and inability to do repeated detection and to resume the detection after a node failure. This paper presents an on-line decentralized algorithm that detects strong conjunctive predicates in a large-scale system. Our algorithm assumes a preconstructed spanning tree in the system, and detects all satisfactions of the predicate in a hierarchical manner. When a node fails or moves and the structure of the spanning tree is changed, our algorithm is able to recover from this situation and continue the detection of further occurrences of the predicate satisfactions. The hierarchical structure of our algorithm also provides a finer-grained monitoring in those large-scale systems where grouping is established and the monitoring happens at the group level. Comparing with other detection algorithms, our algorithm incurs a low space and time cost, which is distributed across all the nodes in the system, and a low message complexity. Our algorithm is particularly beneficial to resource-constrained systems.

Case study of achieving context-awareness based on predicate detection

Currently,to develop context-aware applications that are flexible and adaptable is complex and laborious.There are many unexpected cases to handle. As one of the important approaches to achieve context-awareness,predicate detection can represent context effectively. However,how predicate detection supports the development of context-aware applications on a real device is still largely unknown. In order to cope with these issues,a simple scenario was created.Predicate detection was practically applied to control the car running in a designated environment. The original context was formally modeled and contextual properties were specified into snapshot predicates and sequence predicates. By detecting these specified predicates in the case study,predicate detection was applied to the robot car. The performance analysis shows that predicate detection can effectively detect the car's contextual properties and successfully help the car finish the running task.

Modeling, analyzing and slicing periodic distributed computations

The earlier work on predicate detection has assumed that the given computation is finite. Detecting violation of a liveness predicate requires that the predicate be evaluated on an infinite computation. In this work, we develop the theory and associated algorithms for predicate detection in infinite runs. In practice, an infinite run can be determined in finite time if it consists of a recurrent behavior with some finite prefix. Therefore, our study is restricted to such runs. We introduce the concept of d-diagram, which is a finite representation of infinite directed graphs. Given a d-diagram that represents an infinite distributed computation, we solve the problem of determining if a global predicate ever became true in the computation. The crucial aspect of this problem is the stopping rule that tells us when to conclude that the predicate can never become true in future. We also provide an algorithm to provide vector timestamps to events in the computation for determining the dependency relationship between any two events in the infinite run. Finally, we give an algorithm to compute a slice of a d-diagram which concisely captures all the consistent global states of the computation satisfying the given predicate.

Detecting stable locality-aware predicates

In a large-scale locality-driven network such as in modular robotics and wireless sensor networks, knowing the state of a local area is sometimes necessary due to either interactions being local and driven by neighborhood proximity or the users being interested in the state of a certain region. We define locality-aware predicates (LAP) that aim at detecting a predicate within a specified area. We model the area of interest as the set of processes that are within a breadth-first search tree (BFST) of height k rooted at the initiator process. Although a locality-aware predicate specifies a predicate only within a local area, observing the area consistently requires considering the entire system in a consistent manner. This raises the challenge of making the complexities of the corresponding predicate detection algorithms scale-free, i.e., independent of the size of the system. Since all existing algorithms for getting a consistent view of the system require either a global snapshot of the entire system or vector clocks of the size of the system, a new solution is needed. We focus on stable LAP, which are those LAP that remain true once they become true. We propose a scale-free algorithm to detect stable LAP within a k-height BFST. Our algorithm can detect both stable conjunctive LAP and stable relational LAP. In the process of designing our algorithm, we also propose the first distributed algorithm for building a BFST within an area of interest in a graph, and the first distributed algorithm for recording a consistent sub-cut within the area of interest. This paper demonstrates that LAPs are a natural fit for detecting distributed properties in large-scale distributed systems, and stable LAPs can be practically detected at low cost.

Predicate Detection in Asynchronous Pervasive Environments

An important task in sensor networks is to sense locally to detect global properties that hold at some instant in physical time, namely, Instantaneously. We propose software logical clocks, called strobe clocks, that can be implemented by the middleware when synchronized physical clocks are not available or are too expensive in resource-constrained environments. Strobe clocks come in two flavors--scalar and vector. Let $(n)$ be the number of sensors and $(p)$ be the upper bound on the number of relevant events sensed at a sensor. We propose an algorithm using vector strobes that can detect all occurrences of a conjunctive predicate in time $(O(n^3p))$. The algorithm has some false negatives but this is the best achievable accuracy in the face of race conditions. We also present a variant algorithm using scalar strobes; it needs time $(O(n^2p))$ but may also suffer from some false positives. We provide a characterization of the errors. Both algorithms can also detect relational predicates but with a greater chance of error. The message complexity of strobe clocks (scalar and vector) and both algorithms is $(O(np))$, which is the same as that of reporting each sensed event for detection of the predicate even with synchronized physical clocks. We formalize the physical time modality, Instantaneously, and show its relationship to the logical time modalities Definitely and Possibly.

Подход к восстановлению потока управления запутанной программы

Control flow obfuscation is one of widespread methods used to protect application binary code from analysis. The obfuscation transformations dramatically increase the complexity of separation and recognition of the algorithm and data structures. This paper provides a short survey of obfuscating transformations and tools, essentially the control flow obfuscations like opaque predicates, dispatcher and code virtualization. Our research was concentrated in area of de-obfuscation based on dynamic binary code analysis methods. An approach to locating of potentially opaque predicates and accompanying obfuscations (like dead and redundant code insertion) in program trace is given. The main idea underlying the described method of opaque predicate detection is extraction of predicate code via dynamic program slicing. Next, we apply some heuristics to automatically reduce predicate list, and then our tool provides the analyst with information about potentially opaque predicates found in application binary code. Another control flow obfuscation eliminated by described tool was code virtualization. An algorithm for control flow graph recovery of virtualized code is based on virtual program counter analysis. The corresponding tool was implemented and successfully tested on several applications that were protected via various virtualization obfuscators (VMProtect, CodeVirtualizer, Safengine, etc.). The experimental results described in this paper demonstrate the practical adaptability of implemented method to de-obfuscate virtualized applications.

Immediate detection of predicates in pervasive environments

An important problem in pervasive environments is detecting predicates on sensed variables in an asynchronous distributed setting to determine context and to respond. We do not assume the availability of synchronized physical clocks because they may not be available or may be too expensive for predicate detection in such environments with a (relatively) low event occurrence rate. We address the problem of detecting each occurrence of a global predicate, at the earliest possible instant, by proposing a suite of three on-line middleware protocols having varying degrees of accuracy. We analyze the degree of accuracy for the proposed protocols. The extent of false negatives and false positives is determined by the run-time message processing latencies.

Repeated detection of conjunctive predicates in distributed executions

Given a conjunctive predicate ϕ over a distributed execution, this paper gives an algorithm to detect all interval sets, each interval set containing one interval per process, in which the local values satisfy the Definitely ( ϕ ) modality. The time complexity of the algorithm is O ( n 3 p ) , where n is the number of processes and p is the bound on the number of times a local predicate becomes true at any process. The paper also proves that unlike the Possibly ( ϕ ) modality which admits O ( p n ) solution interval sets, the Definitely ( ϕ ) modality admits O ( n p ) solution interval sets. The paper also gives an on-line test to determine whether all solution interval sets can be detected in polynomial time under arbitrary fine-grained causality-based modality specifications.

Eventually perfect predicate detection in crash-affected finite average response time systems

Monitoring and predicate detection is a fundamental challenge of evaluating whether or not a predicate has held on the state of a distributed system in an execution. We solve eventually perfect predicate detection in a failure-prone system assuming that only the average response time is finite. The solution is based on an eventually accurate failure detection sequencer () which we propose and implement in the finite average response time system. We prove that can solve eventually perfect detection of predicates involving process operational status. This research contributes to identifying realistic detection semantics in a weak partially synchronous model. Our approach has a layered model with which applications have the flexibility to choose appropriate predicate detection algorithms with the possibility to solve different predicate modalities.