23 research outputs found
Characteristics of Conservation Laws for Difference Equations
No full textEach conservation law of a given partial differential equation is determined (up to equivalence) by a function known as the characteristic. This function is used to find conservation laws, to prove equivalence between conservation laws, and to prove the converse of Noether's Theorem. Transferring these results to difference equations is nontrivial, largely because difference operators are not derivations and do not obey the chain rule for derivatives. We show how these problems may be resolved and illustrate various uses of the characteristic. In particular, we establish the converse of Noether's Theorem for difference equations, we show (without taking a continuum limit) that the conservation laws in the infinite family generated by Rasin and Schiff are distinct, and we obtain all five-point conservation laws for the potential Lotka-Volterra equation
Resource Allocation in Streaming Environments
No full textThe proliferation of the Internet and sensor networks has fueled the development of applications that process, analyze, and react to continuous data streams in a near-real-time manner. Examples of such stream applications include network traffic monitoring, intrusion detection, financial services, large-scale reconnaissance, and surveillance.
Unlike tasks in traditional scheduling problems, these stream processing applications are interacting repeating tasks, where iterations of computation are triggered by the arrival of new inputs. Furthermore, these repeated tasks are elastic in the quality of service, and the economic value of a computation depends on the time taken to execute it; for example, an arbitrage opportunity can disappear in seconds. Given limited resources, it is not possible to process all streams without delay. The more resource available to a computation, the less time it takes to process the input, and thus the more value it generates. Therefore, efficiently utilizing a network of limited distributed resources to optimize the net economic value of computations forms a new paradigm in the well-studied field of resource allocation.
We propose using a new performance model and resource reservation system as the solution space, and present two scheduling/resource allocation heuristics for processing streams in a distributed heterogenous computing environment to optimize economic value. Both heuristics are based on market mechanisms; one uses a centralized market and the other decentralized markets. We prove bounds on performance and present measurements to show that the performances of these two heuristics are near-optimal and significantly better than straightforward load-balancing heuristics.</p
Two-layer spherical rubber-metal joints and problems of their calculation features
No full textIntroduction. The article analyses the methods for calculating the characteristics of spherical rubber-metal joints. The authors consider a verified calculation model for determining the stiffness characteristics of spherical rubber-metal joints, both single-layer and double-layer.Materials and methods. The researchers used computer modelling and the finite element method to determine the features of the spherical rubber-metal joints. The possibility of neglecting the deformation of the metal parts of the joint for the modelling purposes was substantiated, which enabled to simplify the calculation model. Moreover, the authors proposed the method for measuring the effect of the elastic layer precompression and determined the values of radial stiffness for single-layer and double-layer rubber-metal joints at different hardness of materials, which coincided with the experimental results. Results. As a result, the authors revealed that with a decrease in the thickness of the rubber layer by assessing the rigidity of the joint, its features were significantly affected by the accuracy of setting the Poisson's ratio. A satisfactory convergence of the radial stiffness of the joint found through the modelling and experimental studies was achieved at a Poisson's ratio equal to 0.499999 (the discrepancy is about 5 %, which is less than the technological spread of rigidity during manufacture). The authors also found out that the rigidity of two-layer rubber-metal joints, similar in size and compensatory capacity to those used in the design of domestic locomotives, should be 6.3 times higher than for existing single-layer ones. Such features would reduce the deformation of rubber by loads exsposion during operation and thereby would solve the problems with the reliability of traction motors suspension units.Discussion and conclusion. Due to the fact that the shape of the free surface of the side faces of two-layer rubber-metal joints before assembly should have small radii of the recesses curvature, further research is needed to select the rational geometry of the free surface of the side faces. The researchers got a utility model patent for the proposed design and manufacturing technology of two-layer rubber-metal joints
Using Real-Time Social Media Technologies to Monitor Levels of Perceived Stress and Emotional State in College Students: A Web-Based Questionnaire Study
No full textUsing Real-Time Social Media Technologies to Monitor Levels of Perceived Stress and Emotional State in College Students: A Web-Based Questionnaire Study
No full textBACKGROUND: College can be stressful for many freshmen as they cope with a variety of stressors. Excess stress can negatively affect both psychological and physical health. Thus, there is a need to find innovative and cost-effective strategies to help identify students experiencing high levels of stress to receive appropriate treatment. Social media use has been rapidly growing, and recent studies have reported that data from these technologies can be used for public health surveillance. Currently, no studies have examined whether Twitter data can be used to monitor stress level and emotional state among college students.
OBJECTIVE: The primary objective of our study was to investigate whether students' perceived levels of stress were associated with the sentiment and emotions of their tweets. The secondary objective was to explore whether students' emotional state was associated with the sentiment and emotions of their tweets.
METHODS: We recruited 181 first-year freshman students aged 18-20 years at University of California, Los Angeles. All participants were asked to complete a questionnaire that assessed their demographic characteristics, levels of stress, and emotional state for the last 7 days. All questionnaires were completed within a 48-hour period. All tweets posted by the participants from that week (November 2 to 8, 2015) were mined and manually categorized based on their sentiment (positive, negative, neutral) and emotion (anger, fear, love, happiness) expressed. Ordinal regressions were used to assess whether weekly levels of stress and emotional states were associated with the percentage of positive, neutral, negative, anger, fear, love, or happiness tweets.
RESULTS: A total of 121 participants completed the survey and were included in our analysis. A total of 1879 tweets were analyzed. A higher level of weekly stress was significantly associated with a greater percentage of negative sentiment tweets (beta=1.7, SE 0.7; P=.02) and tweets containing emotions of fear (beta=2.4, SE 0.9; P=.01) and love (beta=3.6, SE 1.4; P=.01). A greater level of anger was negatively associated with the percentage of positive sentiment (beta=-1.6, SE 0.8; P=.05) and tweets related to the emotions of happiness (beta=-2.2, SE 0.9; P=.02). A greater level of fear was positively associated with the percentage of negative sentiment (beta=1.67, SE 0.7; P=.01), particularly a greater proportion of tweets related to the emotion of fear (beta=2.4, SE 0.8; P=.01). Participants who reported a greater level of love showed a smaller percentage of negative sentiment tweets (beta=-1.3, SE 0.7; P=0.05). Emotions of happiness were positively associated with the percentage of tweets related to the emotion of happiness (beta=-1.8, SE 0.8; P=.02) and negatively associated with percentage of negative sentiment tweets (beta=-1.7, SE 0.7; P=.02) and tweets related to the emotion of fear (beta=-2.8, SE 0.8; P=.01).
CONCLUSIONS: Sentiment and emotions expressed in the tweets have the potential to provide real-time monitoring of stress level and emotional well-being in college students
Energy-efficient design and implementation of turbo codes for wireless sensor network
No full textThe objective of this thesis is to apply near Shannon limit Error-Correcting Codes (ECCs), particularly the turbo-like codes, to energy-constrained wireless devices, for the purpose of extending their lifetime. Conventionally, sophisticated ECCs are applied to applications, such as mobile telephone networks or satellite television networks, to facilitate long range and high throughput wireless communication. For low power applications, such as Wireless Sensor Networks (WSNs), these ECCs were considered due to their high decoder complexities. In particular, the energy efficiency of the sensor nodes in WSNs is one of the most important factors in their design. The processing energy consumption required by high complexity ECCs decoders is a significant drawback, which impacts upon the overall energy consumption of the system. However, as Integrated Circuit (IC) processing technology is scaled down, the processing energy consumed by hardware resources reduces exponentially. As a result, near Shannon limit ECCs have recently begun to be considered for use in WSNs to reduce the transmission energy consumption [1,2]. However, to ensure that the transmission energy consumption reduction granted by the employed ECC makes a positive improvement on the overall energy efficiency of the system, the processing energy consumption must still be carefully considered.The main subject of this thesis is to optimise the design of turbo codes at both an algorithmic and a hardware implementation level for WSN scenarios. The communication requirements of the target WSN applications, such as communication distance, channel throughput, network scale, transmission frequency, network topology, etc, are investigated. Those requirements are important factors for designing a channel coding system. Especially when energy resources are limited, the trade-off between the requirements placed on different parameters must be carefully considered, in order to minimise the overall energy consumption. Moreover, based on this investigation, the advantages of employing near Shannon limit ECCs in WSNs are discussed. Low complexity and energy-efficient hardware implementations of the ECC decoders are essential for the target applications
An ontology enhanced parallel SVM for scalable spam filter training
No full textThis is the post-print version of the final paper published in Neurocomputing. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Spam, under a variety of shapes and forms, continues to inflict increased damage. Varying approaches including Support Vector Machine (SVM) techniques have been proposed for spam filter training and classification. However, SVM training is a computationally intensive process. This paper presents a MapReduce based parallel SVM algorithm for scalable spam filter training. By distributing, processing and optimizing the subsets of the training data across multiple participating computer nodes, the parallel SVM reduces the training time significantly. Ontology semantics are employed to minimize the impact of accuracy degradation when distributing the training data among a number of SVM classifiers. Experimental results show that ontology based augmentation improves the accuracy level of the parallel SVM beyond the original sequential counterpart
A resource aware distributed LSI algorithm for scalable information retrieval
No full textThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Latent Semantic Indexing (LSI) is one of the popular techniques in the information retrieval fields. Different from the traditional information retrieval techniques, LSI is not based on the keyword matching simply. It uses statistics and algebraic computations. Based on Singular Value Decomposition (SVD), the higher dimensional matrix is converted to a lower dimensional approximate matrix, of which the noises could be filtered. And also the issues of synonymy and polysemy in the traditional techniques can be overcome based on the investigations of the terms related with the documents. However, it is notable that LSI suffers a scalability issue due to the computing complexity of SVD.
This thesis presents a resource aware distributed LSI algorithm MR-LSI which can solve the scalability issue using Hadoop framework based on the distributed computing model MapReduce. It also solves the overhead issue caused by the involved clustering algorithm. The evaluations indicate that MR-LSI can gain significant enhancement compared to the other strategies on processing large scale of documents. One remarkable advantage of Hadoop is that it supports heterogeneous computing environments so that the issue of unbalanced load among nodes is highlighted. Therefore, a load balancing algorithm based on genetic algorithm for balancing load in static environment is proposed. The results show that it can improve the performance of a cluster according to heterogeneity levels.
Considering dynamic Hadoop environments, a dynamic load balancing strategy with varying window size has been proposed. The algorithm works depending on data selecting decision and modeling Hadoop parameters and working mechanisms. Employing improved genetic algorithm for achieving optimized scheduler, the algorithm enhances the performance of a cluster with certain heterogeneity levels
Self-organizing distributed workflow management
No full textThe proliferation of service-oriented architectures in the last decade has brought forward an important class of sophisticated distributed applications that are founded on
the idea of composing multiple simple services into a complex, coherent whole. Such applications spanning multiple service invocations can be most effectively realized by means of workflows. When it comes to high performance workflow execution, distribution (outscaling) of services is a key concept and also a very straightforward advantage of the workflow paradigm. Concretely, both the constituent services of the workflow and the system that manages their invocations have to be distributed across an environment of computational devices. In a wide spectrum of applications, that entail heterogeneity of the encompassed computational devices, e.g., modern emergency management, invocations of optimal service instances in conjunction to their reliability are
fundamental prerequisites of distributed workflow management.
At the center of this thesis is a formal model that defines the distributed (i.e., scalable) execution of workflows. To extend this model for reliability in a novel way, which
does not affect the scalability of execution, the Safety-Ring system service is presented.
The idea behind Safety-Ring is to offer recovery for a wide range of node failures, which
host active services of running workflows. To this end, the Safety-Ring provides a scalable, reliable, and consistent data store that is used for the storage of workflow execution state. The novel failure-recovery mechanism features effective reliability such that can
be applied on the nodes that host the Safety-Ring service themselves, thus we say the Safety-Ring is self-healing.
To apply the reliable (and distributed) execution model, enhanced by Safety-Ring, to heterogeneous node environments, that are predominantly composed of mobile de-
vices, this thesis presents the Compass data access protocol. In providing scalable data lookup for its maintained data, the Safety-Ring assumes network runtime characteristics which are rather stable, and thus Safety-Ring implicitly optimizes for the number of
queried nodes. Especially in mobile applications, where node network connectivity dynamically changes, data access protocols should aim at reducing the overall data lookup
latency, rather than the number of queried nodes. Compass introduces latency optimal paths to each node, which dynamically adapt to changing network characteristics. The
scalable data lookup of Safety-Ring is not affected.
In case distributed execution of workflows spans services of continuous (stateful) type, their reliability is decoupled from the Safety-Ring. Since such service types are
predominantly featured by devices of limited resources, novel approaches to resource conservative recovery of failures for continuous services have to be provided. This thesis builds on proven recovery techniques, such as passive-standby, so as to enhance them for redundancy of the continuous state and thus improve the overall reliability of the system. In doing so the redundancy of state is enforced by means of a lightweight, in terms of network overhead, consistency protocol which allows for its application in resource limited node environments.
In order to improve the execution performance of distributed workflows, in terms of throughput, this thesis offers a novel concept to services distribution. At the heart of our approach lie decentralized controllers that autonomously perform dynamic reconfiguration of the execution environment in terms of available services. This primarily affects the Safety-Ring service and all application services. Thereby, the goals of the controllers
are to prevent workflow execution bottlenecks and unnecessary service deployments that waste resources. Since the controllers are equipped at any node in the system and
can affect any other node of the system we say that the distributed workflow execution model is self-optimizing.
Finally, all the presented concepts are implemented within the context of the OSIRIS distributed workflow engine and quantitatively evaluated in a series of experiments.
The results of experiments confirm the benefits of our concepts for the distributed workflow execution model
