Stream Operators Research Articles

Analysis of Influence of Tilt Angle on the Distribution of Water Droplets Diameters in a Spray Generated by the Turbo Master 52 Nozzle

This paper presents studies on the influence of the nozzle tilt angle on the distribution of water droplets diameters in a spray generated by the Turbo Master 52 nozzle. Analysis was limited to the most representative points located on the defined ellipses, constituting sprinkling surface of streams for the set angle of the nozzle, spray angle and flow rate. Among the others the following is discussed in the paper: study subject, study method, research stand and the course of studies. The studies were conducted for three different nozzle tilt angles of 20o, 30o and 40o, three different flow rates 200 dm3/min, 300 dm3/min and 400 dm3/min, and two different spray angles 30o and 60o. The studies also included investigation of solid jet type for the same three nozzle angles and three flow rates. However, it is not covered in this article. The obtained results are presented in a tabular and graphical form. Based on the analysis of results the conclusion are formulated, important not only for the theoretical considerations but also in practice, especially in the context of water stream operation by the firefighters during rescue and fire-fighting actions.

Reinforcement of Event Streams by Obfuscation over Multitudinous Correlations

Event processing is an approach of capturing and processing the data about events. The data may come from multiple origins in complex event processing systems and transmitted through multiple security authorities. Present event processing systems are failing in conserving the privacy constraints of incoming event streams in a sequence of eventually applied stream operations. This problem emerges in large-scale distributed applications like a logistic chain where event processing operators may be escalated over multitudinous security domains .This paper presents a frail access management in multi-hop event processing networks. Literally this paper offers a solution to maintain privacy constraints even when the events turn to correlated complex events. The obfuscation value calculated using Bayesian Network is used to decide whether inheritance of access requirement is needed. The implementation offers methods to enhance the obfuscation calculation and to increase the Bayesian Network size to measure obfuscation over multitudinous correlations that reinforces the event streams.

Serial control of CNC machines

In this paper a new method of the serial control of CNC machines is proposed. Actuators are controlled locally and the role of the central computer is limited to sending commands to the controller instead of sending it directly to actuators. It has been achieved with the use of the serial protocol with the use of the USB port. The taken approach leads to more reliable operation because commands are buffered and no synchronization between command stream and actuators operation is needed.

Kafka, Samza and the Unix philosophy of distributed data

Apache Kafka is a scalable message broker, and Apache Samza is a stream processing framework built upon Kafka. They are widely used as infrastructure for implementing personalized online services and real-time predictive analytics. Besides providing high throughput and low latency, Kafka and Samza are designed with operational robustness and long-term maintenance of applications in mind. In this paper we explain the reasoning behind the design of Kafka and Samza, which allow complex applications to be built by composing a small number of simple primitives – replicated logs and stream operators. We draw parallels between the design of Kafka and Samza, batch processing pipelines, database architecture, and the design philosophy of Unix.

Supported Liquid Phase Catalyst coating in micro flow Mizoroki–Heck reaction

A Supported Liquid Phase Catalyst (SLPC) coating was successfully applied for the Mizoroki–Heck reaction in micro flow. Foremost, extended on stream operation was enabled and the on stream performance stability was verified. Stable catalytic activity was achieved during two consecutive runs totaling 50h, after an initial stabilization period. Further support for the catalytic stability was provided by the fact that no leached Pd was detected in the product. Highest obtained conversion was 94% at 230°C and a 26min residence time. When conversion was plotted versus residence time, the reaction was shown to fit the predictions of the kinetic model. To optimize the performance of the flow system, reaction conditions and different ligands for the catalyst were initially investigated in batch, as well as various different substrates. Ethylene glycol was found to be most effective as the solvent film, while the use of water led to degradation of the silica support.

Changing engines in midstream

With the addition of lambda expressions and the Stream API in Java 8, Java has gained a powerful and expressive query language that operates over in-memory collections of Java objects, making the transformation and analysis of data more convenient, scalable and efficient. In this paper, we build on Java 8 Stream and add a DistributableStream abstraction that supports federated query execution over an extensible set of distributed compute engines. Each query eventually results in the creation of a materialized result that is returned either as a local object or as an engine defined distributed Java Collection that can be saved and/or used as a source for future queries. Distinctively, DistributableStream supports the changing of compute engines both between and within a query, allowing different parts of a computation to be executed on different platforms. At execution time, the query is organized as a sequence of pipelined stages, each stage potentially running on a different engine. Each node that is part of a stage executes its portion of the computation on the data available locally or produced by the previous stage of the computation. This approach allows for computations to be assigned to engines based on pricing, data locality, and resource availability. Coupled with the inherent laziness of stream operations, this brings great flexibility to query planning and separates the semantics of the query from the details of the engine used to execute it. We currently support three engines, Local, Apache Hadoop MapReduce and Oracle Coherence, and we illustrate how new engines and data sources can be added.

A lattice based solution of the collisional Boltzmann equation with applications to microchannel flows

An alternative approach for solution of the collisional Boltzmann equation for a lattice architecture is presented. In the proposed method, termed the collisional lattice Boltzmann method (cLBM), the effects of spatial transport are accounted for via a streaming operator, using a lattice framework, and the effects of detailed collisional interactions are accounted for using the full collision operator of the Boltzmann equation. The latter feature is in contrast to the conventional lattice Boltzmann methods (LBMs) where collisional interactions are modeled via simple equilibrium based relaxation models (e.g. BGK). The underlying distribution function is represented using weights and fixed velocity abscissas according to the lattice structure. These weights are evolved based on constraints on the evolution of generalized moments of velocity according to the collisional Boltzmann equation. It can be shown that the collision integral can be reduced to a summation of elementary integrals, which can be analytically evaluated. The proposed method is validated using studies of canonical microchannel Couette and Poiseuille flows (both body force and pressure driven) and the results are found to be in good agreement with those obtained from conventional LBMs and experiments where available. Unlike conventional LBMs, the proposed method does not involve any equilibrium based approximations and hence can be useful for simulation of highly nonequilibrium flows (for a range of Knudsen numbers) using a lattice framework.

Modeling and predicting performance of high performance computing applications on hardware accelerators

Hybrid-core systems speedup applications by offloading certain compute operations that can run faster on hardware accelerators. However, such systems require significant programming and porting effort to gain a performance benefit from the accelerators. Therefore, prior to porting it is prudent to investigate the predicted performance benefit of accelerators for a given workload. To address this problem we present a performance-modeling framework that predicts the application performance rapidly and accurately for hybrid-core systems. We present predictions for two full-scale HPC applications—HYCOM and Milc. Our results for two accelerators (GPU and FPGA) show that gather/scatter and stream operations can speedup by as much as a factor of 15 and overall compute time of Milc and HYCOM improve by 3.4% and 20%, respectively. We also show that in order to benefit from the accelerators, 70% of the latency of data transfer time between the CPU and the accelerators needs to be overcome.

Curracurrong: a stream programming environment for wireless sensor networks

SUMMARYThe technological advances in wireless sensor network (WSN) enable the development of complex applications including health monitoring, environmental sampling, and disaster area monitoring. WSN applications deploy battery‐powered sensors at remote locations for long periods. The development of energy‐efficient and complex WSN applications therefore requires in‐depth embedded systems programming skills that are normally not found in domain experts. So that this challenge can be overcome, programming environments for WSN need to offer a high degree of productivity, flexibility, and efficiency at the same time. In this work, we present Curracurrong, a development environment for WSNs that is based on expressing queries with stream programming. A query is represented as a stream graph consisting of stream operators and communication channels. Curracurrong provides an extensible stream operator library that adapts to a wide range of applications. It uses a novel placement algorithm that optimizes the energy consumption on sensor nodes. Through a case study, we demonstrate the productivity and flexibility of our system. We conduct experiments that evaluate the energy efficiency of our optimized operator placement algorithm. Copyright © 2012 John Wiley & Sons, Ltd.

A Class of Contracting Stream Operators

In (Tucker, J. V. and Zucker, J. I. (2007) Computability of analog networks. Theoret. Comput. Sci., 371, 115–146; Tucker, J. V. and Zucker, J. I. (2011) Continuity of operators on continuous and discrete time streams. Theoret. Comput. Sci., 412, 3378–3403), Tucker and Zucker present a model for the semantics of analog networks operating on streams from topological algebras. Central to their model is a parametrized stream operator representing the network along with a theory that concerns the existence, uniqueness, continuity and computability of a fixed point of that stream operator. We narrow the scope of this paper from general topological algebras to algebras of streams that assume values only from a Banach space. This restriction facilitates the definition of a fairly broad class of stream operators to which the theory described in the above two papers applies. As a demonstration in their original work, the authors provide two case studies: analog networks that model the behavior of simple mass-spring-damper systems. The case studies showcase the theory well, but they seem to require the imposition of somewhat peculiar conditions on the parameters (the masses, the spring constants and the damping coefficients). The extra conditions—while not catastrophic to the case studies—make them somewhat unsatisfying. We show here that while their original mass–spring–damper models do not fall within our new class, they can be trivially reconfigured into equivalent models that do. This modification obviates the extra conditions on the parameters.

Advantage of Ni/SBA-15 catalyst over Ni/MgO catalyst in terms of catalyst stability due to release of water during nitrobenzene hydrogenation to aniline

Two catalysts, Ni/SBA-15 and Ni/MgO were prepared by wet impregnation technique with 5 wt.% Ni loading in each catalyst. These were tested for nitrobenzene hydrogenation to aniline reaction under vapor phase at atmospheric pressure. Ni/MgO suffered a huge loss in the activity (conversion) during time on stream study even though the Ni dispersion is larger compared to that in SBA-15 supported catalyst. TPR studies of used catalysts confirm coking of the catalysts. The superior catalytic activity in terms of conversion and selectivity during time on stream operation exhibited by Ni/SBA-15 catalyst is due to the hydrophobic nature of this catalyst (resistant to water generated during the reaction) and the effect of coking is not significant. Hydrophobic nature of SBA-15 makes Ni/SBA-15 an ideal catalyst for nitrobenzene hydrogenation to aniline. ► The hydrophobic nature of SBA-15 makes Ni/SBA-15 a robust catalyst. ► Deactivation of Ni/MgO is due to adsorption of water generated during the reaction. ► The role of carbon deposition during the reaction is insignificant on the activity. ► Strong interaction between Ni and MgO favors higher Ni dispersion.

Massive scale-out of expensive continuous queries

Scalable execution of expensive continuous queries over massive data streams requires input streams to be split into parallel sub-streams. The query operators are continuously executed in parallel over these sub-streams. Stream splitting involves both partitioning and replication of incoming tuples, depending on how the continuous query is parallelized. We provide a stream splitting operator that enables such customized stream splitting. However, it is critical that the stream splitting itself keeps up with input streams of high volume. This is a problem when the stream splitting predicates have some costs. Therefore, to enable customized splitting of high-volume streams, we introduce a parallelized stream splitting operator, called parasplit. We investigate the performance of parasplit using a cost model and experimentally. Based on these results, a heuristic is devised to automatically parallelize the execution of parasplit. We show that the maximum stream rate of parasplit is network bound, and that the parallelization is energy efficient. Finally, the scalability of our approach is experimentally demonstrated on the Linear Road Benchmark, showing an order of magnitude higher stream processing rate over previously published results, allowing at least 512 expressways.

Dispatching stream operators in parallel execution of continuous queries

Data stream is a continuous, rapid, time-varying sequence of data elements which should be processed in an online manner. These matters are under research in Data Stream Management Systems (DSMSs). Single processor DSMSs cannot satisfy data stream applications’ requirements properly. Main shortcomings are tuple latency, tuple loss, and throughput. In our previous publications, we introduced parallel execution of continuous queries to overcome these problems via performance improvement, especially in terms of tuple latency. We scheduled operators in an event-driven manner which caused system performance reduction in periods between consecutive scheduling instances. In this paper, a continuous scheduling method (dispatching) is presented to be more compatible with the continuous nature of data streams as well as queries to improve system adaptivity and performance. In a multiprocessing environment, the dispatching method forces processing nodes (logical machines) to send partially-processed tuples to next machines with minimum workload to execute the next operator on them. So, operator scheduling is done continuously and dynamically for each tuple processed by each operator. The dispatching method is described, formally presented, and its correctness is proved. Also, it is modeled in PetriNets and is evaluated via simulation. Results show that the dispatching method significantly improves system performance in terms of tuple latency, throughput, and tuple loss. Furthermore, the fluctuation of system performance parameters (against variation of system and stream characteristics) diminishes considerably and leads to high adaptivity with the underlying system.

Ruthenium catalyst on carbon nanofiber support layers for use in silicon-based structured microreactors. Part II: Catalytic reduction of bromate contaminants in aqueous phase

Catalyst layers were synthesized inside a structured channel of silicon based microreactor and used to remove bromate contaminants in water. It is demonstrated that Ru/CNF based catalyst is active for bromate reduction, resulting in turn over frequencies (TOFs) higher than conventional powdered catalyst, i.e. activated carbon (AC). This enhanced catalytic performance can be attributed to improve mass transfer properties of entangled CNF layers with macroporous (open) structure, which offer enhanced accessibility to all the Ru active sites in contrast to the poor accessibility of active sites in the case of AC support material.Although promising catalytic activity of Ru/CNF catalyst was observed for bromate reduction, a continuing deactivation was observed during 5h time on stream operation. A variety of characterization techniques including TEM, XPS, TPR, ICP probed that in addition to catalyst sintering, formation of catalytically inactive Ru(OH)x phase on catalyst surface was an important reason of this deactivation. Use of higher alcohols proved to be beneficial for achieving stability of Ru/CNF catalyst for bromate reduction, however with reduced levels of overall activity.

Concrete stream calculus: An extended study

AbstractThis paper shows how to reason about streams concisely and precisely. Streams, infinite sequences of elements, live in a coworld: they are given by a coinductive datatype, operations on streams are implemented by corecursive programs, and proofs are typically concocted using coinduction. This paper offers an alternative to coinduction. Suitably restricted, stream equations possessunique solutions. This property gives rise to a simple and attractive proof technique, essentially bringing equational reasoning to the coworld. We redevelop the theory of recurrences, finite calculus and generating functions using streams and stream operators, building on the cornerstone of unique solutions. The paper contains a smörgåsbord of examples: we study recursion elimination, investigate the binary carry sequence, explore Sprague-Grundy numbers and present two proofs of Moessner's Theorem. The calculations benefit from the rich structure of streams. As the type of streams is an applicative functor we can effortlessly lift operations and their properties to streams. In combination with Haskell's facilities for overloading, this greatly contributes to conciseness of notation. The development is indeed constructive: streams and stream operators are implemented in Haskell, usually by one-liners. The resulting calculus or library, if you wish, is elegant and fun to use.

Facing the catalytic combustion of CH4/H2 mixtures into monoliths

Catalytic combustion of methane mixed with hydrogen in micro-scale channels is becoming a key research topic, for various portable power generation devices that could replace current batteries to meet the increasing demand for more efficient, longer lasting and more environmentally friendly energy-consuming utilizations. The present work deals with the investigation on the performance of catalyst 2% Pd over 5% LaMnO3·ZrO2 (PLZ), lined on silicon carbide (SC) or cordierite (CD) monoliths, for the CH4/H2/air lean mixtures oxidation. The bare and coated monoliths were tested into a lab-microreactor designed to provide a favourable environment for microscale combustion of various CH4/H2/air lean mixtures to reach high power density (7.6MWthm−3; GHSV 16,000h−1). The main goal of the catalytic combustion tests was to select the best settings to achieve stable combustion conditions at the lowest possible temperature, i.e., full CH4 conversion with the minimum H2 concentration in the reactive mixture, accompanied by the lowest possible CO concentration.Depending on the thermal conductivity of the tested monoliths, the existence of the steady-state multiplicity was verified, mainly when the H2 concentration was quite low. Basically, CD monoliths exhibited shorter ignition times compared to SC ones, due to the formation of spatially localized hot spots that promoted catalytic ignition. At the same time, the CD monoliths required shorter times to reach steady-state. But SC materials assured longer time on stream operations. The presence of the catalyst lined on both monoliths allowed reaching lower CO emissions. The best results belonged to the coated SiC monolith, with very low H2 concentration in the mixtures.

The Innovation Iteration Grid

A common misconception about innovation is that the innovation process lacks pragmatism. Innovation professionals use soft concepts applied in fuzzy ways with too much emphasis on unproven approaches to solving problems. Perhaps because of the unconventional approaches taken by practitioners of innovation, business executives have generally segregated innovators from main stream operations, recognizing the importance of innovation, but not comfortable with the approach that innovation professionals often employ in getting to their ends. This paper discusses an approach to innovation that has the ability to firmly tie the strategy, mission or vision of the organization to the innovation process. An approach that allows you to take the “Universal Intentions” (mission, vision, goals objectives or strategies) to an iterative process that allows innovation iteration to optimization of a process.

Semantics and implementation of continuous sliding window queries over data streams

In recent years the processing of continuous queries over potentially infinite data streams has attracted a lot of research attention. We observed that the majority of work addresses individual stream operations and system-related issues rather than the development of a general-purpose basis for stream processing systems. Furthermore, example continuous queries are often formulated in some declarative query language without specifying the underlying semantics precisely enough. To overcome these deficiencies, this article presents a consistent and powerful operator algebra for data streams which ensures that continuous queries have well-defined, deterministic results. In analogy to traditional database systems, we distinguish between a logical and a physical operator algebra. While the logical algebra specifies the semantics of the individual operators in a descriptive but concrete way over temporal multisets, the physical algebra provides efficient implementations in the form of stream-to-stream operators. By adapting and enhancing research from temporal databases to meet the challenging requirements in streaming applications, we are able to carry over the conventional transformation rules from relational databases to stream processing. For this reason, our approach not only makes it possible to express continuous queries with a sound semantics, but also provides a solid foundation for query optimization, one of the major research topics in the stream community. Since this article seamlessly explains the steps from query formulation to query execution, it outlines the innovative features and operational functionality implemented in our state-of-the-art stream processing infrastructure.

Time-Stamp Management and Query Execution in Data Stream Management Systems

Relational query languages can effectively express continuous queries on data streams after modest extensions. However, implementing such queries efficiently in data stream management systems requires major changes in execution models and optimization techniques. In particular, finer-granularity execution models that are conducive to effective time-stamp management and response-time optimization must replace databases' relational algebra schemes. This article introduces such a model and uses it to solve the idle-waiting problems of data stream operators, such as unions, joins, and aggregates over windows with slides.

Functional pearl

Streams, infinite sequences of elements, live in a coworld: they are given by a coinductive data type, operations on streams are implemented by corecursive programs, and proofs are conducted using coinduction. But there is more to it: suitably restricted, stream equations possess unique solutions , a fact that is not very widely appreciated. We show that this property gives rise to a simple and attractive proof technique essentially bringing equational reasoning to the coworld. In fact, we redevelop the theory of recurrences, finite calculus and generating functions using streams and stream operators building on the cornerstone of unique solutions. The development is constructive: streams and stream operators are implemented in Haskell, usually by one-liners. The resulting calculus or library, if you wish, is elegant and fun to use. Finally, we rephrase the proof of uniqueness using generalised algebraic data types.