Journal articles: 'Dataflow patterns'

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Meddah, Ishak H. A., Khaled Belkadi, and Mohamed Amine Boudia. "Efficient Implementation of Hadoop MapReduce based Business Process Dataflow." International Journal of Decision Support System Technology 9, no. 1 (2017): 49–60. http://dx.doi.org/10.4018/ijdsst.2017010104.

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Hadoop MapReduce is one of the solutions for the process of large and big data, with-it the authors can analyze and process data, it does this by distributing the computational in a large set of machines. Process mining provides an important bridge between data mining and business process analysis, his techniques allow for mining data information from event logs. Firstly, the work consists to mine small patterns from a log traces, those patterns are the workflow of the execution traces of business process. The authors' work is an amelioration of the existing techniques who mine only one general workflow, the workflow present the general traces of two web applications; they use existing techniques; the patterns are represented by finite state automaton; the final model is the combination of only two types of patterns whom are represented by the regular expressions. Secondly, the authors compute these patterns in parallel, and then combine those patterns using MapReduce, they have two parts the first is the Map Step, they mine patterns from execution traces and the second is the combination of these small patterns as reduce step. The results are promising; they show that the approach is scalable, general and precise. It reduces the execution time by the use of Hadoop MapReduce Framework.

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Rostami, Mohammad, Somayyeh Ehteshami, Fatemeh Yaghoobi, Farid Saghari, and Samaneh Dezhdar. "Proposing a Algorithm for Finding Repetitive Patterns in Web Dataflow." International Journal of Software Engineering and Its Applications 9, no. 7 (2015): 181–92. http://dx.doi.org/10.14257/ijseia.2015.9.7.19.

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Sane, Nimish, Hojin Kee, Gunasekaran Seetharaman, and Shuvra S. Bhattacharyya. "Topological Patterns for Scalable Representation and Analysis of Dataflow Graphs." Journal of Signal Processing Systems 65, no. 2 (2011): 229–44. http://dx.doi.org/10.1007/s11265-011-0610-1.

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Wang, Lai-Huei, Chung-Ching Shen, Shenpei Wu, and Shuvra S. Bhattacharyya. "Parameterized Scheduling of Topological Patterns in Signal Processing Dataflow Graphs." Journal of Signal Processing Systems 71, no. 3 (2012): 275–86. http://dx.doi.org/10.1007/s11265-012-0719-x.

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Tsoeunyane, Lekhobola, Simon Winberg, and Michael Inggs. "Automatic Configurable Hardware Code Generation for Software-Defined Radios." Computers 7, no. 4 (2018): 53. http://dx.doi.org/10.3390/computers7040053.

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The development of software-defined radio (SDR) systems using field-programmable gate arrays (FPGAs) compels designers to reuse pre-existing Intellectual Property (IP) cores in order to meet time-to-market and design efficiency requirements. However, the low-level development difficulties associated with FPGAs hinder productivity, even when the designer is experienced with hardware design. These low-level difficulties include non-standard interfacing methods, component communication and synchronization challenges, complicated timing constraints and processing blocks that need to be customized through time-consuming design tweaks. In this paper, we present a methodology for automated and behavioral integration of dedicated IP cores for rapid prototyping of SDR applications. To maintain high performance of the SDR designs, our methodology integrates IP cores using characteristics of the dataflow model of computation (MoC), namely the static dataflow with access patterns (SDF-AP). We show how the dataflow is mapped onto the low-level model of hardware by efficiently applying low-level based optimizations and using a formal analysis technique that guarantees the correctness of the generated solutions. Furthermore, we demonstrate the capability of our automated hardware design approach by developing eight SDR applications in VHDL. The results show that well-optimized designs are generated and that this can improve productivity while also conserving the hardware resources used.

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Hentrich, David, Erdal Oruklu, and Jafar Saniie. "Program diagramming and fundamental programming patterns for a polymorphic computing dataflow processor." Journal of Computer Languages 65 (August 2021): 101052. http://dx.doi.org/10.1016/j.cola.2021.101052.

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Bispo, J., J. Cardoso, and J. Monteiro. "Hardware Pipelining of Repetitive Patterns in Processor Instruction Traces." Journal of Integrated Circuits and Systems 8, no. 1 (2013): 22–31. http://dx.doi.org/10.29292/jics.v8i1.373.

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Dynamic partitioning is a promising technique where computations are transparently moved from a Gene- ral Purpose Processor (GPP) to a coprocessor during application execution. To be effective, the mapping of computations to the coprocessor needs to consider aggressive optimizations. One of the mapping opti- mizations is loop pipelining, a technique extensively studied and known to allow substantial performance improvements. This paper describes a technique for pipelining Megablocks, a type of runtime loop deve- loped for dynamic partitioning. The technique transforms the body of Mega-blocks into an acyclic dataflow graph which can be fully pipe-lined and is based on the atomic execution of loop iterations. For a set of 9 ben- chmarks without memory operations, we generated pipelined hardware versions of the loops and esti-mate that the presented loop pipelining technique increases the average speedup of non-pipelined coprocessor accelerated designs from 1.6× to 2.2×. For a larger set of 61 benchmarks which include memory operations, we estimate through simulation a speedup increase from 2.5× to 5.6× with this technique.

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Wang, G. Q., R. Allen, H. A. Andrade, and A. Sangiovanni-Vincentelli. "Communication storage optimization for static dataflow with access patterns under periodic scheduling and throughput constraint." Computers & Electrical Engineering 40, no. 6 (2014): 1858–73. http://dx.doi.org/10.1016/j.compeleceng.2014.05.002.

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Alam, A. K. M. Mubashwir, Sagar Sharma, and Keke Chen. "SGX-MR: Regulating Dataflows for Protecting Access Patterns of Data-Intensive SGX Applications." Proceedings on Privacy Enhancing Technologies 2021, no. 1 (2021): 5–20. http://dx.doi.org/10.2478/popets-2021-0002.

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AbstractIntel SGX has been a popular trusted execution environment (TEE) for protecting the integrity and confidentiality of applications running on untrusted platforms such as cloud. However, the access patterns of SGX-based programs can still be observed by adversaries, which may leak important information for successful attacks. Researchers have been experimenting with Oblivious RAM (ORAM) to address the privacy of access patterns. ORAM is a powerful low-level primitive that provides application-agnostic protection for any I/O operations, however, at a high cost. We find that some application-specific access patterns, such as sequential block I/O, do not provide additional information to adversaries. Others, such as sorting, can be replaced with specific oblivious algorithms that are more efficient than ORAM. The challenge is that developers may need to look into all the details of application-specific access patterns to design suitable solutions, which is time-consuming and error-prone. In this paper, we present the lightweight SGX based MapReduce (SGX-MR) approach that regulates the dataflow of data-intensive SGX applications for easier application-level access-pattern analysis and protection. It uses the MapReduce framework to cover a large class of data-intensive applications, and the entire framework can be implemented with a small memory footprint. With this framework, we have examined the stages of data processing, identified the access patterns that need protection, and designed corresponding efficient protection methods. Our experiments show that SGX-MR based applications are much more efficient than the ORAM-based implementations.

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Miller, Julian, Lukas Trümper, Christian Terboven, and Matthias S. Müller. "A Theoretical Model for Global Optimization of Parallel Algorithms." Mathematics 9, no. 14 (2021): 1685. http://dx.doi.org/10.3390/math9141685.

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With the quickly evolving hardware landscape of high-performance computing (HPC) and its increasing specialization, the implementation of efficient software applications becomes more challenging. This is especially prevalent for domain scientists and may hinder the advances in large-scale simulation software. One idea to overcome these challenges is through software abstraction. We present a parallel algorithm model that allows for global optimization of their synchronization and dataflow and optimal mapping to complex and heterogeneous architectures. The presented model strictly separates the structure of an algorithm from its executed functions. It utilizes a hierarchical decomposition of parallel design patterns as well-established building blocks for algorithmic structures and captures them in an abstract pattern tree (APT). A data-centric flow graph is constructed based on the APT, which acts as an intermediate representation for rich and automated structural transformations. We demonstrate the applicability of this model to three representative algorithms and show runtime speedups between 1.83 and 2.45 on a typical heterogeneous CPU/GPU architecture.

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Yang, Zhao Hong, Qing Xiao, Yun Zhan Gong, Da Hai Jin, and Ya Wen Wang. "The Research of an Abstract Semantic Framework for Defect Detecting." Advanced Materials Research 186 (January 2011): 536–40. http://dx.doi.org/10.4028/www.scientific.net/amr.186.536.

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This paper proposes a non-relational abstract semantic framework. It uses interval set to represent the value of numerical variables and complete lattice to represent Boolean variables and reference variables. It presents the abstract computation method of basic expressions and the nodes of control flow graph. It uses function summaries to represent the context information of function call needed by defects detecting. Based on the results of abstract computation, it uses extended state machine to define defect patterns and proposes a path-sensitive method based on dataflow analysis to detect defects. It avoids the combination explosion of full path analysis by merging the conditions of identical property state at join points in the CFG. Practical test results show that the proposed methods have features of high efficiency, low false positive and low false negative.

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Arndt, Timothy, Shi-Kuo Chang, Angela Guercio, and Paolo Maresca. "An XML-Based Approach to Multimedia Software Engineering for Distance Learning." International Journal of Distance Education Technologies 1, no. 1 (2003): 40–62. http://dx.doi.org/10.4018/jdet.2003010103.

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Multimedia Software Engineering (MSE) is a new frontier for both Software Engineering (SE) and Visual Languages (VL). In fact multimedia software engineering can be considered as the discipline for systematic specification, design, substitution and verification of visual patterns. In this paper we concentrate on the first of these possibilities, distance learning. One aim of this paper is to demonstrate how it is possible to design and implement conplex multimedia software systems for distance learning using a Teleaction Object transformer based on XML technology applying a Component-Based Multimedia Software Engineering approach. The paper shows a complete process of dataflow transformation that represents TAO in different ways (text, TAOML, etc.) and at different levels of abstraction. The transformation process is a reversible one. A component-based tool architecture is also discussed.

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Massoud, Rana, Riccardo Berta, Stefan Poslad, Alessandro De Gloria, and Francesco Bellotti. "IoT Sensing for Reality-Enhanced Serious Games, a Fuel-Efficient Drive Use Case." Sensors 21, no. 10 (2021): 3559. http://dx.doi.org/10.3390/s21103559.

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Internet of Things technologies are spurring new types of instructional games, namely reality-enhanced serious games (RESGs), that support training directly in the field. This paper investigates a key feature of RESGs, i.e., user performance evaluation using real data, and studies an application of RESGs for promoting fuel-efficient driving, using fuel consumption as an indicator of driver performance. In particular, we propose a reference model for supporting a novel smart sensing dataflow involving the combination of two modules, based on machine learning, to be employed in RESGs in parallel and in real-time. The first module concerns quantitative performance assessment, while the second one targets verbal recommendation. For the assessment module, we compared the performance of three well-established machine learning algorithms: support vector regression, random forest and artificial neural networks. The experiments show that random forest achieves a slightly better performance assessment correlation than the others but requires a higher inference time. The instant recommendation module, implemented using fuzzy logic, triggers advice when inefficient driving patterns are detected. The dataflow has been tested with data from the enviroCar public dataset, exploiting on board diagnostic II (OBD II) standard vehicular interface information. The data covers various driving environments and vehicle models, which makes the system robust for real-world conditions. The results show the feasibility and effectiveness of the proposed approach, attaining a high estimation correlation (R2 = 0.99, with random forest) and punctual verbal feedback to the driver. An important word of caution concerns users’ privacy, as the modules rely on sensitive personal data, and provide information that by no means should be misused.

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Aridoss, Manimaran. "Defensive Mechanism Against DDoS Attack to Preserve Resource Availability for IoT Applications." International Journal of Handheld Computing Research 8, no. 4 (2017): 40–51. http://dx.doi.org/10.4018/ijhcr.2017100104.

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The major challenge of Internet of Things (IoT) generated data is its hypervisor level vulnerabilities. Malicious VM deployment and termination are so simple due to its multitenant shared nature and distributed elastic cloud features. These features enable the attackers to launch Distributed Denial of Service attacks to degrade cloud server performance. Attack detection techniques are applied to the VMs that are used by malicious tenants to hold the cloud resources by launching DDoS attacks at data center subnets. Traditional dataflow-based attack detection methods rely on the similarities of incoming requests which consist of IP and TCP header information flows. The proposed approach classifies the status patterns of malicious VMs and ideal VMs to identify the attackers. In this article, information theory is used to calculate the entropy value of the malicious virtual machines for detecting attack behaviors. Experimental results prove that the proposed system works well against DDoS attacks in IoT applications.

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Figueroa, Pablo. "Insights on the Design of InTml." Presence: Teleoperators and Virtual Environments 19, no. 2 (2010): 118–30. http://dx.doi.org/10.1162/pres.19.2.118.

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This paper describes some details about the design of InTml, the interaction techniques markup language. We explain three main elements in its architecture: a simple mixed reality (MR) based component model, a communication model between components that allows fusion of multimodal information at a fine level of granularity, and an indirection mechanism for dataflows that is useful to keep state inside a dataflow. We also briefly discuss the advantages we have found in the use of formal methods, model driven development, and encapsulation mechanisms. The purpose of this description is to make explicit the design rationale of these mechanisms, which may be fruitful for other developments in our field.

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Halappanavar, Mahantesh, John Feo, Oreste Villa, Antonino Tumeo, and Alex Pothen. "Approximate weighted matching on emerging manycore and multithreaded architectures." International Journal of High Performance Computing Applications 26, no. 4 (2012): 413–30. http://dx.doi.org/10.1177/1094342012452893.

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Graph matching is a prototypical combinatorial problem with many applications in high-performance scientific computing. Optimal algorithms for computing matchings are challenging to parallelize. Approximation algorithms are amenable to parallelization and are therefore important to compute matchings for large-scale problems. Approximation algorithms also generate nearly optimal solutions that are sufficient for many applications. In this paper we present multithreaded algorithms for computing half-approximate weighted matching on state-of-the-art multicore (Intel Nehalem and AMD Magny-Cours), manycore (Nvidia Tesla and Nvidia Fermi), and massively multithreaded (Cray XMT) platforms. We provide two implementations: the first uses shared work queues and is suited for all platforms; and the second implementation, based on dataflow principles, exploits special features available on the Cray XMT. Using a carefully chosen dataset that exhibits characteristics from a wide range of applications, we show scalable performance across different platforms. In particular, for one instance of the input, an R-MAT graph (RMAT-G), we show speedups of about [Formula: see text] on [Formula: see text] cores of an AMD Magny-Cours, [Formula: see text] on [Formula: see text] cores of Intel Nehalem, [Formula: see text] on Nvidia Tesla and [Formula: see text] on Nvidia Fermi relative to one core of Intel Nehalem, and [Formula: see text] on [Formula: see text] processors of Cray XMT. We demonstrate strong as well as weak scaling for graphs with up to a billion edges using up to 12,800 threads. We avoid excessive fine-tuning for each platform and retain the basic structure of the algorithm uniformly across platforms. An exception is the dataflow algorithm designed specifically for the Cray XMT. To the best of the authors' knowledge, this is the first such large-scale study of the half-approximate weighted matching problem on multithreaded platforms. Driven by the critical enabling role of combinatorial algorithms such as matching in scientific computing and the emergence of informatics applications, there is a growing demand to support irregular computations on current and future computing platforms. In this context, we evaluate the capability of emerging multithreaded platforms to tolerate latency induced by irregular memory access patterns, and to support fine-grained parallelism via light-weight synchronization mechanisms. By contrasting the architectural features of these platforms against the Cray XMT, which is specifically designed to support irregular memory-intensive applications, we delineate the impact of these choices on performance.

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Hamon, Grégoire. "Synchronous Dataflow Pattern Matching." Electronic Notes in Theoretical Computer Science 153, no. 4 (2006): 37–54. http://dx.doi.org/10.1016/j.entcs.2006.02.024.

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Pramanik, S. "A Hardware Pattern Matching Algorithm On A Dataflow." Computer Journal 28, no. 3 (1985): 264–69. http://dx.doi.org/10.1093/comjnl/28.3.264.

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Wang, Guiling, Yanbo Han, Zhongmei Zhang, and Shouli Zhang. "A Dataflow-Pattern-Based Recommendation Framework for Data Service Mashup." IEEE Transactions on Services Computing 8, no. 6 (2015): 889–902. http://dx.doi.org/10.1109/tsc.2015.2471307.

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Boukhelifa, Nadia, and Peter J. Rodgers. "A Model and Software System for Coordinated and Multiple Views in Exploratory Visualization." Information Visualization 2, no. 4 (2003): 258–69. http://dx.doi.org/10.1057/palgrave.ivs.9500057.

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This paper describes a model for expressing coordination in multiple view visualization systems. We present the model and describe a prototype implementation that illustrates the features of the model. Current visualization systems tend to have an informal and inconsistent approach to coordination. Our model takes a formal approach to describing widely used coordination concepts. The model is based on views sharing abstract objects such as the visualization parameters of the dataflow model. Additionaly, this paper describes how current coordinations in exploratory visualization work and how novel coordinations can be constructed using our model.

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Cudennec, Loïc, and Renaud Sirdey. "Parallelism Reduction Based on Pattern Substitution in Dataflow Oriented Programming Languages." Procedia Computer Science 9 (2012): 146–55. http://dx.doi.org/10.1016/j.procs.2012.04.016.

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Ding, Dandan, Fuchang Liu, Honggang Qi, and Zhengwei Yao. "An FPGA-friendly CABAC-encoding architecture with dataflow modelling programming." Imaging Science Journal 66, no. 6 (2018): 346–54. http://dx.doi.org/10.1080/13682199.2018.1477486.

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Figueroa, Pablo, Walter F. Bischof, Pierre Boulanger, H. James Hoover, and Robyn Taylor. "InTml: A Dataflow Oriented Development System for Virtual Reality Applications." Presence: Teleoperators and Virtual Environments 17, no. 5 (2008): 492–511. http://dx.doi.org/10.1162/pres.17.5.492.

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This paper presents our research on the Interaction Techniques Markup Language (InTml). Our final goal in this work is to find ways to evolve and fit virtual reality (VR) applications over heterogeneous hardware platforms, a process we call retargeting. Toward this goal, we have developed a hardware-independent, component-based, formal model that describes the execution of VR applications; an XML language for describing complex and implementation-independent VR applications; a methodology for InTml-based development; a manual way to isolate and replace interaction techniques as a contribution to VR retargeting; and a set of tools for development support. This paper describes these topics and states future directions of our research.

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SHAPIRO, LINDA G., ROBERT M. HARALICK, and MICHAEL J. GOULISH. "INSIGHT: A DATAFLOW LANGUAGE FOR PROGRAMMING VISION ALGORITHMS IN A RECONFIGURABLE COMPUTATIONAL NETWORK." International Journal of Pattern Recognition and Artificial Intelligence 01, no. 03n04 (1987): 335–50. http://dx.doi.org/10.1142/s0218001487000230.

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Machine vision systems used in industrial applications must execute their algorithms in real time to perform such tasks as inspecting a wire bond or guiding a robot to install a part on a car body moving along a conveyer. The real time speed is achieved by employing simple-minded algorithms and by designing parallel architectures and parallel algorithms for some tasks. The majority of the work on parallel architectures has been limited to architectures that support image processing, but not mid- or high-level vision In order for more complex vision algorithms to execute in real time, a more flexible architecture is needed. Our conceptual approach to the problem is a reconfigurable computational network. Each configuration of the network implements an algorithm or class of algorithms A high-level language expresses the algorithms in a relational form that can be easily translated to the specification for a configuration. The language must be able to encode low-, mid-, and high-level vision algorithms and to efficiently handle not only pixel data, but also higher level structures. In this paper we describe a dataflow language called INSIGHT, which we have designed to meet these needs, and give several examples of parallel machine vision algorithms expressed in the language.

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S�rot, Jocelyn, Georges Qu�not, and Bertrand Zavidovique. "Functional programming on a dataflow architecture: Applications in real-time image processing." Machine Vision and Applications 7, no. 1 (1993): 44–56. http://dx.doi.org/10.1007/bf01212416.

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Yviquel, Hervé, Jani Boutellier, Mickaël Raulet, and Emmanuel Casseau. "Automated design of networks of transport-triggered architecture processors using dynamic dataflow programs." Signal Processing: Image Communication 28, no. 10 (2013): 1295–302. http://dx.doi.org/10.1016/j.image.2013.08.013.

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ISHIDA, Naoto, Takashi ISHIO, Yuta NAKAMURA, Shinji KAWAGUCHI, Tetsuya KANDA, and Katsuro INOUE. "Visualization of Inter-Module Dataflow through Global Variables for Source Code Review." IEICE Transactions on Information and Systems E101.D, no. 12 (2018): 3238–41. http://dx.doi.org/10.1587/transinf.2018edl8104.

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Yu, Bowen, and Claudio T. Silva. "FlowSense: A Natural Language Interface for Visual Data Exploration within a Dataflow System." IEEE Transactions on Visualization and Computer Graphics 26, no. 1 (2020): 1–11. http://dx.doi.org/10.1109/tvcg.2019.2934668.

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Al Hilli, F., and A. K. Malik. "Oesophageal cancer in Bahrain." Eastern Mediterranean Health Journal 9, no. 3 (2021): 372–76. http://dx.doi.org/10.26719/2003.9.3.372.

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Datafrom all 148 cases of oesophageal cancer in Bahrain during 1952-99 were analysed according to patient sex and age and site and histological pattern of tumour, and compared with other Gulf countries. In Bahrain, oesophageal cancer accounted for 2.6% of malignant neoplasms. The female: male ratio was 1.8: 1, and the majority of patients were >/=51 years and </=70 years of age. The lower and upper third of the oesophagus were the most and least frequently involved sites, respectively. Squamous carcinoma [males] and adenocarcinoma [females] were the main histological types. There is varying consistency between these data and those of other Gulf countries having similar anthropological and demographic profiles. A prospective study may help to better underst and the aetiology of the disease and inform preventive policies

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Thompson, Paul M., Ann Mackay, Dominic J. Tollit, Simon Enderby, and Philip S. Hammond. "The influence of body size and sex on the characteristics of harbour seal foraging trips." Canadian Journal of Zoology 76, no. 6 (1998): 1044–53. http://dx.doi.org/10.1139/z98-035.

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Most pinnipeds disperse from centralised terrestrial sites to forage at sea, but the factors that result in variation inforaging-trip characteristics remain unclear. We investigated the influence of sex and body size on the summer foraging activityof radio-tagged harbour seals (Phoca vitulina) from Scotland. Mean foraging-trip duration (range 17257 h) was stronglycorrelated with mean foraging range (range 4.355.0 km), but both were significantly shorter for females. The proportion oftime spent at sea, mean trip duration, and mean foraging range were all positively related to body size. Comparison with datafrom other study areas suggests that both environmental and endogenous factors shape foraging characteristics in this species.These sex and body size related differences in activity pattern and foraging range have important implications for themethodologies currently used to assess the population size, population energy requirements, and diet composition of coastalpinnipeds.

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Fitriana, Nur, Dwidjono Hadi Darwanto, and Slamet Hartono. "ANALISIS PERTUMBUHAN EKONOMI DAN KEUNGGULAN SEKTOR PERTANIAN INDONESIA." Agro Ekonomi 15, no. 1 (2017): 63. http://dx.doi.org/10.22146/jae.18172.

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The study aims: (1) to measure the growth rate of economic sector based on Gross Domestic Product; (2) to determine contribution of economic sector to GDP; (3) to measure contribution trend of economic sector of GDP and to determine basic sectors inprovinces of Indonesia. The data used is secondary datafrom Badan Pusat Statistik, i.e. Gross Regional Domestic Product and Gross Domestic Product according with 1993 constant price. Data included overall provinces in Indonesia among 19842003. Table analysis, Location Quotient, shift-share, and Klassen Typology were used to analyze. The results are: (1) growth rate o/GDP is positively fluctuated, except at 1998 due to economic crisis; (2) contribution ofagricultural sector; mining and quarrying sector; and services sector weredecreased Contribution of manufacturing industries sector; electricity, gasand water supply sector; trade, restaurant and hotel sector; and transportation and communication sector were increased. Contribution of construction sector and finance and rent of building and business sector werefluctuated; (3) overall sector follow quadratic pattern, exceptfinance, building rent, and business sector that follow linear pattern; (4) agricultural sector was the basic sector in ·26 provinces, except in East Kalimantan, Banten, WestJava and Jakarta.

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Zuo, Zhiqiang, Kai Wang, Aftab Hussain, et al. "Systemizing Interprocedural Static Analysis of Large-scale Systems Code with Graspan." ACM Transactions on Computer Systems 38, no. 1-2 (2021): 1–39. http://dx.doi.org/10.1145/3466820.

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There is more than a decade-long history of using static analysis to find bugs in systems such as Linux. Most of the existing static analyses developed for these systems are simple checkers that find bugs based on pattern matching. Despite the presence of many sophisticated interprocedural analyses, few of them have been employed to improve checkers for systems code due to their complex implementations and poor scalability. In this article, we revisit the scalability problem of interprocedural static analysis from a “Big Data” perspective. That is, we turn sophisticated code analysis into Big Data analytics and leverage novel data processing techniques to solve this traditional programming language problem. We propose Graspan , a disk-based parallel graph system that uses an edge-pair centric computation model to compute dynamic transitive closures on very large program graphs. We develop two backends for Graspan, namely, Graspan-C running on CPUs and Graspan-G on GPUs, and present their designs in the article. Graspan-C can analyze large-scale systems code on any commodity PC, while, if GPUs are available, Graspan-G can be readily used to achieve orders of magnitude speedup by harnessing a GPU’s massive parallelism. We have implemented fully context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases written in multiple languages such as Linux and Apache Hadoop demonstrates that their Graspan implementations are language-independent, scale to millions of lines of code, and are much simpler than their original implementations. Moreover, we show that these analyses can be used to uncover many real-world bugs in large-scale systems code.

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Lanza, Elizabeth, and Hirut Woldemariam. "Multilingualism and Local Literacy Practices in Ethiopia: Language contact in regulated and unregulated spaces." Multilingual Margins: A journal of multilingualism from the periphery 1, no. 1 (2018): 55. http://dx.doi.org/10.14426/mm.v1i1.22.

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The study of the linguistic landscape has provided a new dimension to theories andissues related to multilingualism, including language policy. In this growing field ofinquiry, however, not enough attention has been given to the linguistic landscape insites in the Global South. Since one of the aims of literacy studies is to reveal the varietyand social patternings of practices, there is a need to compare linguistic landscape datawith other various textual materials. In this article, we present linguistic landscape datafrom two federal regional capitals in Ethiopia that demonstrate multilingual languageuse. We also compare the linguistic contact patterns with those found in schoolbooksused in the same region. Such a comparison involves language use in unregulatedas well as in regulated spaces (see Sebba 2009). Regional ethnically based languagesare now being used in new arenas, including the linguistic landscape and educationbecause of a new language policy promoting the use and development of regionallanguages. The two regional capitals provide privileged sites for examining theproducts of local literacy practices, involving values, attitudes, ideologies, and socialrelationships. We discuss the results in light of various ideologies and argue for thespeaker-writer’s active mobilisation of multilingual resources in new language arenas.

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Chen, Qinyu, Yuxiang Fu, Wenqing Song, et al. "An Efficient Streaming Accelerator for Low Bit-Width Convolutional Neural Networks." Electronics 8, no. 4 (2019): 371. http://dx.doi.org/10.3390/electronics8040371.

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Convolutional Neural Networks (CNNs) have been widely applied in various fields, such as image recognition, speech processing, as well as in many big-data analysis tasks. However, their large size and intensive computation hinder their deployment in hardware, especially on the embedded systems with stringent latency, power, and area requirements. To address this issue, low bit-width CNNs are proposed as a highly competitive candidate. In this paper, we propose an efficient, scalable accelerator for low bit-width CNNs based on a parallel streaming architecture. With a novel coarse grain task partitioning (CGTP) strategy, the proposed accelerator with heterogeneous computing units, supporting multi-pattern dataflows, can nearly double the throughput for various CNN models on average. Besides, a hardware-friendly algorithm is proposed to simplify the activation and quantification process, which can reduce the power dissipation and area overhead. Based on the optimized algorithm, an efficient reconfigurable three-stage activation-quantification-pooling (AQP) unit with the low power staged blocking strategy is developed, which can process activation, quantification, and max-pooling operations simultaneously. Moreover, an interleaving memory scheduling scheme is proposed to well support the streaming architecture. The accelerator is implemented with TSMC 40 nm technology with a core size of 0.17 mm 2 . It can achieve 7.03 TOPS/W energy efficiency and 4.14 TOPS/mm 2 area efficiency at 100.1 mW, which makes it a promising design for the embedded devices.

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Lee, Min-June, Barry M. Popkin, and Soowon Kim. "The unique aspects of the nutrition transition in South Korea: the retention of healthful elements in their traditional diet." Public Health Nutrition 5, no. 1a (2002): 197–203. http://dx.doi.org/10.1079/phn2001294.

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AbstractObjective:The purposes of this paper are to describe the unique aspects of the nutrition transition in South Korea, including trends in food consumption and obesity, patterns of morbidity and mortality; to focus on efforts to maintain the traditional diet in the midst of rapid economic growth and the introduction of Western culture; and to provide insights for other countries.Design:We analysed secondary dietary intake, anthropometric, morbidity and mortality datafrom published reports and articles.Results:In South Korea, the level and rate of increase in fat intake have remained very low, whereas vegetable intake has been high and fruit intake has increased greatly. South Kore also has a relatively low prevalence of obesity compared with other Asian countries. The traditional Korean diet is a low-fat and high-vegetable diet. Therefore, the government and nutrition specialists have been initiating numerous efforts to advertise and teach the public that the traditional diet is a healthy diet. They are also working on revival of the traditional dietusing an approach that is acceptable to contemporary Koreans.Conclusions:The nutrition transition in South Korea is unique. A range of government, nutrition specialists and some private organisation efforts has worked to retain healthful elements of the traditional diet in South Korea. The continued low level of total fat in the overalldiet and the high intake of fruits and vegetables bode well for South Korea.

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Rost, Christopher, Kevin Gomez, Matthias Täschner, et al. "Distributed temporal graph analytics with GRADOOP." VLDB Journal, May 19, 2021. http://dx.doi.org/10.1007/s00778-021-00667-4.

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AbstractTemporal property graphs are graphs whose structure and properties change over time. Temporal graph datasets tend to be large due to stored historical information, asking for scalable analysis capabilities. We give a complete overview of Gradoop, a graph dataflow system for scalable, distributed analytics of temporal property graphs which has been continuously developed since 2005. Its graph model TPGM allows bitemporal modeling not only of vertices and edges but also of graph collections. A declarative analytical language called GrALa allows analysts to flexibly define analytical graph workflows by composing different operators that support temporal graph analysis. Built on a distributed dataflow system, large temporal graphs can be processed on a shared-nothing cluster. We present the system architecture of Gradoop, its data model TPGM with composable temporal graph operators, like snapshot, difference, pattern matching, graph grouping and several implementation details. We evaluate the performance and scalability of selected operators and a composed workflow for synthetic and real-world temporal graphs with up to 283 M vertices and 1.8 B edges, and a graph lifetime of about 8 years with up to 20 M new edges per year. We also reflect on lessons learned from the Gradoop effort.

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Rebrus, Péter, and Miklós Törkenczy. "Monotonicity and the limits of disharmony." Proceedings of the Annual Meetings on Phonology 2 (June 1, 2016). http://dx.doi.org/10.3765/amp.v2i0.3769.

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The attested front/back harmony systems are monotonic in the sense thatthe harmony function that assigns the values front and back to suffixes ingiven harmonic stem contexts is subject to a constraint that only permitscontiguous patterns of values on a universally fixed scale of harmoniccontexts (ranging from the prototypical back harmony context [...B]_ tothe prototypical front one [...F]_ ). We argue that monotonicity alsoconstrains variation (harmony patterns involving the harmonic valuefront/back) and show that in Hungarian the harmonic properties of a stem(front, back, variable front/back) are inherited by the forms derived fromthe stem by inflection or derivation. This paradigm uniformity effect(Harmonic Uniformity) results in subpatterns of front/back harmony whichalso conform to monotonicity. We demonstrate this using frequency datafrom a corpus study.

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Olson, Don, Willem Van der Mei, Sungwoo Lim, Carol Yoon, Melissa Kull, and Marivel Davila. "Monitoring child mental health related emergency department visits in New York City." Online Journal of Public Health Informatics 9, no. 1 (2017). http://dx.doi.org/10.5210/ojphi.v9i1.7720.

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ObjectiveTo assess the use of syndromic surveillance to assess trends inmental health-related emergency department (ED) visits amongschool-aged children and adolescents in New York City (NYC).IntroductionFrom 2001-2011, mental health-related hospitalizations and EDvisits increased among United States children nationwide [1]. Duringthis period, mental health-related hospitalizations among NYCchildren increased nearly 23% [2]. To estimate mental health-relatedED visits in NYC and assess the use of syndromic surveillance chiefcomplaint data to monitor these visits, we compared trends from anear real-time syndromic system with those from a less timely, codedED visit database.MethodsThe NYC ED syndromic surveillance system receives anonymizedpatient chief complaint and basic demographic data for nearly everyED visit citywide to provide timely surveillance information tohealth authorities. Using NYC ED syndromic surveillance datafrom 2003-2015, we applied previously developed definitions forgeneral psychiatric syndromes. We aggregated ED visits by agegroup (5-12 years, 13-17 years, and 18-20 years), geography, andtemporality. Syndromic data were compared with Statewide Planningand Research Collaborative System (SPARCS) data from 2006-2014which reported mental health diagnosis (ICD-9), treatment, service,and basic demographics for patients visiting facilities in NYC. Usingthese two data sources, we compared daily visit patterns and annualtrends overall as well as stratified by age group, area-based poverty(ZIP code), and time of visit.ResultsBoth syndromic surveillance and SPARCS data for NYC showedan increasing trend during the period. While both showed relativeincreases with similar slopes, mental health-related chief complaintdata captured fewer overall visits than the ICD-9 coded SPARCSdata. Trends in syndromic data during 2003-2015 differed by age-group and area-based poverty, e.g., among children ages 5-12 yearsthe annual proportion of mental health-related ED visits increasedroughly 3-fold from 1.2% to 3.8% in the poorest areas, which wasgreater than the increase in the richest areas (1.7% to 2.6%). Seasonal,day-of-week, and school holiday patterns found far fewer visits duringthe periods of NYC public school breaks (Figure).ConclusionsWe conclude that syndromic surveillance data can provide areliable indicator of mental health-related ED visit trends. Thesefindings suggest potential benefit of syndromic surveillance data asthey may help capture temporal and spatial clustering of events in amuch more timely manner than the >1 year delay in availability ofED discharge data. Next steps include a qualitative study exploringthe causes of these patterns and the role of various factors drivingthem, as well as use of patient disposition and matched data to bettercharacterize ED visit patient outcomes.

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Journal articles on the topic 'Dataflow patterns'

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