2,044 research outputs found
UA66/3/3 Journal of the A. C. M.
No full textJournal created by and about the WKU Association for Computing Machinery a student organization sponsored by WKU Computer Science
The Impact of Name-Matching and Blocking on Author Disambiguation
No full textIn this work, we address the problem of blocking in the context of author name disambiguation. We describe a framework that formalizes different ways of name-matching to determine which names could potentially refer to the same author. We focus on name variations that follow from specifying a name with different completeness (i.e. full first name or only initial). We extend this framework by a simple way to define traditional, new and custom blocking schemes. Then, we evaluate different old and new schemes in the Web of Science. In this context we define and compare a new type of blocking schemes. Based on these results, we discuss the question whether name-matching can be used in blocking evaluation as a replacement of annotated author identifiers. Finally, we argue that blocking can have a strong impact on the application and evaluation of author disambiguation
Enterprise Crowd Computing for Human Aided Chatbots
No full textchatbot is an example of cognitive computing system that emulates human conversations to provide informational, transactional,and conversational services. Despite their widespread adoption, chatbots still suffer from a number of performance issue due to limitations with their programming and training. In this paper we discuss Human Aided Chatbots, i.e. chatbots that rely on humans in the loop to operate. Human Aided Chatbots exploit human intelligence, brought for instance by crowd workers or full-time employees, to fill the gaps caused by limitations of fully automated solutions. A recent example of Human Aided Chatbots is Facebook M. To achieve broader adoption, Human Aided Chatbots must overcome a number of issues, including scalability, low-latency, and privacy. In this short paper, we discuss how Crowd Computing performed in the enterprise could help overcoming such issues. We present some recentfi ndings in thefi eld of Enterprise Crowd Computing, and introduce ECrowd, a platform for enterprise crowd computingdesigned for gathering training data for cognitive systems.Accepted author manuscriptWeb Information System
Interdisciplinary teaching and learning in computing science: three years of experience in the MoCSSy program
No full textOriginally appeared in the WCCCE '12: Proceedings of the Seventeenth Western Canadian Conference on Computing Education (Vancouver, BC, Canada; 4-5 May, 2012).
Simon Fraser University introduced the Modelling of Complex Social Systems Program (MoCSSy) as an interdisciplinary research program aimed at complex societal issues. Since its inception, the MoCSSy program has engaged a number of students from computing science, who worked on problems brought by their peers in fields such as obesity and criminology. In this paper, we introduce the organization and structure of MoCSSy, pointing to the importance of computing science in meeting the specific goals and objectives of the Program. Through an analysis of surveys completed with MoCSSy students, we conducted a preliminary assessment on the impact of the program for computing science majors and non majors. We found that the program successfully achieved many of its goals, as computing science majors and non-majors appreciated working with each other and made academic contributions that would not have been possible without this synergy. Finally, we analyze current challenges and identify a strategy for the way forward.Peer reviewedFinal article publishe
WARio: efficient code generation for intermittent computing
No full textIntermittently operating embedded computing platforms powered by energy harvesting require software frameworks to protect from errors caused by Write After Read (WAR) dependencies. A powerful method of code protection for systems with non-volatile main memory utilizes compiler analysis to insert a checkpoint inside each WAR violation in the code. However, such software frameworks are oblivious to the code structure - -and therefore, inefficient - -when many consecutive WAR violations exist. Our insight is that by transforming the input code, i.e., moving individual write operations from unique WARs close to each other, we can significantly reduce the number of checkpoints. This idea is the foundation for WARio: a set of compiler transformations for efficient code generation for intermittent computing. WARio, on average, reduces checkpoint overhead by 58%, and up to 88%, compared to the state of the art across various benchmarks.Embedded System
IoT resource-aware orchestration framework for edge computing
No full textExisting edge computing solutions in the Internet of Things (IoT) domain operate with the control plane residing in the cloud and edge as a slave that executes the workload deployed by the cloud. The growing diversity in the IoT applications requires the edge to be able to run multiple distinct workloads corresponding to the dedicated inputs it receives, each catering to a specific task. Achieving this with the current approach poses a limitation as the cloud lacks the local knowledge at the edge and sharing this knowledge regularly between the edge and the cloud will defeat the very purpose of edge computing, i.e., low latency, less network congestion and data privacy. To solve this problem, we propose an orchestration framework for edge computing that enables the edge to actively initiate and orchestrate the workloads on request by using the local knowledge available in the form of IoT resources at the edge.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Dataintensive SystemsInformation and Communication Technolog
Efficient GPU Acceleration for Computing Maximal Exact Matches in Long DNA Reads
No full textThe seeding heuristic is widely used in many DNA analysis applications to speed up the analysis time. In many applications, seeding takes a substantial amount of the total execution time. In this paper, we present an efficient GPU implementation for computing maximal exact matching (MEM) seeds in long DNA reads. We applied various optimizations to reduce the number of GPU global memory accesses and to avoid redundant computation. Our implementation also extracts maximum parallelism from the MEM computation tasks. We tested our implementation using data from the state-of-the-art third generation Pacbio DNA sequencers, which produces DNA reads that are tens of kilobases long. Our implementation is up to 9x faster for computing MEM seeds as compared to the fastest CPU implementation running on a server-grade machine with 24 threads. Computing suffix array intervals (first part of MEM computation) is up to 3x faster whereas calculating the location of the match (second part) is up to 9x faster. The implementation is publicly available at https://github.com/nahmedraja/GPUseed.Accepted author manuscriptQuantum & Computer EngineeringQCD/Almudever Lab(OLD)Quantum Computer ArchitecturesComputer Engineerin
Deterministic (1+)-approximate maximum matching with poly(1/) passes in the semi-streaming model and beyond
No full textFunding Information: The second author of this work was supported by the Swiss NSF Grant under Grant No. P400P2_191122/1. Most of this work was done while the author was affiliated with MIT. The third author was supported in part by the Academy of Finland under Grant No. 334238. Publisher Copyright: © 2022 Owner/Author.We present a deterministic (1+ϵ)-approximate maximum matching algorithm in poly(1/ϵ) passes in the semi-streaming model, solving the long-standing open problem of breaking the exponential barrier in the dependence on 1/ϵ. Our algorithm exponentially improves on the well-known randomized (1/ϵ)O(1/ϵ)-pass algorithm from the seminal work by McGregor [APPROX05], the recent deterministic algorithm by Tirodkar with the same pass complexity [FSTTCS18]. Up to polynomial factors in 1/ϵ, our work matches the state-of-the-art deterministic (logn / loglogn) · (1/ϵ)-pass algorithm by Ahn and Guha [TOPC18], that is allowed a dependence on the number of nodes n. Our result also makes progress on the Open Problem 60 at sublinear.info. Moreover, we design a general framework that simulates our approach for the streaming setting in other models of computation. This framework requires access to an algorithm computing a maximal matching and an algorithm for processing disjoint ( 1 / ϵ)-size connected components. Instantiating our framework in CONGEST yields a (logn, 1/ϵ) round algorithm for computing (1+ϵ)-approximate maximum matching. In terms of the dependence on 1/ϵ, this result improves exponentially state-of-the-art result by Lotker, Patt-Shamir, and Pettie [LPSP15]. Our framework leads to the same quality of improvement in the context of the Massively Parallel Computation model as well.Peer reviewe
Migrating Business Logic to an Incremental Computing DSL: A Case Study
No full textTo provide empirical evidence to what extent migration of business logic to an incremental computing language (ICL) is useful, we report on a case study on a learning management system. Our contribution is to analyze a real-life project, how migrating business logic to an ICL affects information system validatability, performance, and development effort.We find that the migrated code has better validatability; it is straightforward to establish that a program ‘does the right thing’. Moreover, the performance is better than the previous hand-written incremental computing solution. The effort spent on modeling business logic is reduced, but integrating that logic in the application and tuning performance takes considerable effort. Thus, the ICL separates the concerns of business logic and performance, but does not reduce effort.Accepted Author ManuscriptProgramming Language
Towards a framework for cloud computing use by governments: Leaders, followers and laggers
No full textThere are large varieties of governmental organizations using clouds in different ways. The purpose of this article is to explore and classify the types of public organizations using cloud computing. This will help to improve our understanding of cloud adoption and use by governments. For this, a systematic review of literature on cloud government (CloudGov) was performed by searching for articles in several databases. The review resulted into the main elements of the framework for classifying cloud use. In addition, using diffusion of innovation and institutional theory a categorization of public organizations was made. When applying the CloudGov framework empirically in government organizations, we identified three types of organizations: Leaders, Followers and Laggers. The types differ in various ways including their technology expertise, attitude towards innovation and level of political support. In further research, we recommend investigating which drivers influence the type of CloudGov users and generalize the framework to other contexts.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Information and Communication Technolog
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